176  
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Break
Thu May 9th 08:00 AM -- 12:00 PM @ None
Registration Desk Open
Invited Talk
Thu May 9th 09:00 -- 09:45 AM @ Great Hall AD
Learning Natural Language Interfaces with Neural Models
Mirella Lapata
Oral
Thu May 9th 09:45 -- 10:00 AM @ Great Hall AD
Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu · Angela Fan · Alexei Baevski · Yann Dauphin · Michael Auli
Oral
Thu May 9th 10:00 -- 10:15 AM @ Great Hall AD
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao · Chuang Gan · Pushmeet Kohli · Joshua B Tenenbaum · Jiajun Wu
Oral
Thu May 9th 10:15 -- 10:30 AM @ Great Hall AD
Smoothing the Geometry of Probabilistic Box Embeddings
Xiang Li · Luke Vilnis · Dongxu Zhang · Michael Boratko · Andrew McCallum
Break
Thu May 9th 10:30 -- 11:00 AM @ Hall B-1
Coffee Break (Rescheduled from 10:30 to 10:45)
Oral
Thu May 9th 10:30 -- 10:45 AM @ Great Hall AD
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen · Shawn Tan · Alessandro Sordoni · Aaron Courville
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #1
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Florian Mai · Lukas Galke · Ansgar Scherp
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #2
Kernel RNN Learning (KeRNL)
Christopher Roth · Ingmar Kanitscheider · Ila Fiete
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #3
Unsupervised Hyper-alignment for Multilingual Word Embeddings
Jean Alaux-Lorain · Edouard Grave · marco cuturi · Armand Joulin
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #4
textTOvec: DEEP CONTEXTUALIZED NEURAL AUTOREGRESSIVE TOPIC MODELS OF LANGUAGE WITH DISTRIBUTED COMPOSITIONAL PRIOR
Pankaj Gupta · Yatin Chaudhary · Florian Buettner · Hinrich Schuetze
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #5
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Victor Zhong · Caiming Xiong · Nitish Shirish Keskar · richard socher
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #6
Generalized Tensor Models for Recurrent Neural Networks
Valentin Khrulkov · Oleksii Hrinchuk · Ivan Oseledets
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #7
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
Joshua Michalenko · Ameesh Shah · Abhinav Verma · Richard Baraniuk · Swarat Chaudhuri · Ankit B Patel
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #8
Top-Down Neural Model For Formulae
Karel Chvalovský
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #9
Variational Smoothing in Recurrent Neural Network Language Models
Lingpeng Kong · Gábor Melis · Wang Ling · Lei Yu · Dani Yogatama
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #10
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Sang-Woo Lee · Tong Gao · Sohee Yang · Jaejun Yoo · Jung-Woo Ha
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #11
DOM-Q-NET: Grounded RL on Structured Language
Sheng Jia · Jamie Kiros · Jimmy Ba
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #12
Poincare Glove: Hyperbolic Word Embeddings
Alexandru Tifrea · Gary Bécigneul · Octavian Ganea
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #13
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen · Shawn Tan · Alessandro Sordoni · Aaron Courville
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #14
Learning Recurrent Binary/Ternary Weights
Arash Ardakani · Zhengyun Ji · Sean Smithson · Brett Meyer · Warren J Gross
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #15
FlowQA: Grasping Flow in History for Conversational Machine Comprehension
Hsin-Yuan Huang · Eunsol Choi · Wen-tau Yih
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #16
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder
Caio Corro · Ivan Titov
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #17
Adaptive Input Representations for Neural Language Modeling
Alexei Baevski · Michael Auli
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #18
Neural Speed Reading with Structural-Jump-LSTM
Christian Hansen · Casper Hansen · Stephen Alstrup · Jakob Simonsen · Christina Lioma
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #19
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling
Josue Nassar · Scott W Linderman · Monica Bugallo · Il M Park
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #20
Multilingual Neural Machine Translation with Knowledge Distillation
Xu Tan · Yi Ren · Di He · Tao Qin · Zhou Zhao · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #21
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Bhargav Kanuparthi · Devansh Arpit · Giancarlo Kerg · Nan Rosemary Ke · Ioannis Mitliagkas · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #23
Multiple-Attribute Text Rewriting
Guillaume Lample · Sandeep Subramanian · Eric Smith · Ludovic Denoyer · Marc'Aurelio Ranzato · Y-Lan Boureau
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #24
RNNs implicitly implement tensor-product representations
Tom McCoy · Tal Linzen · Ewan Dunbar · Paul Smolensky
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #25
Complement Objective Training
Hao-Yun Chen · Pei-Hsin Wang · Chun-Hao Liu · Shih-Chieh Chang · Jia-Yu Pan · Yu-Ting Chen · Wei Wei · Da-Cheng Juan
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #26
Adversarial Audio Synthesis
Chris Donahue · Julian McAuley · Miller Puckette
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #27
A Generative Model For Electron Paths
John Bradshaw · Matt Kusner · Brooks Paige · Marwin Segler · José Miguel Hernández Lobato
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #28
Smoothing the Geometry of Probabilistic Box Embeddings
Xiang Li · Luke Vilnis · Dongxu Zhang · Michael Boratko · Andrew McCallum
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #29
Wizard of Wikipedia: Knowledge-Powered Conversational Agents
Emily Dinan · Stephen Roller · Kurt Shuster · Angela Fan · Michael Auli · Jason Weston
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #30
Understanding Composition of Word Embeddings via Tensor Decomposition
Abraham Frandsen · Rong Ge
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #31
Multilingual Neural Machine Translation With Soft Decoupled Encoding
Xinyi Wang · Hieu Pham · Philip Arthur · Graham Neubig
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #32
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao · Chuang Gan · Pushmeet Kohli · Joshua B Tenenbaum · Jiajun Wu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #33
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang · Bo Li · Pin-Yu Chen · Dawn Song
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #34
Harmonic Unpaired Image-to-image Translation
Rui Zhang · Tomas Pfister · Li-Jia Li
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #35
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Thomas Miconi · Aditya Rawal · Jeff Clune · Kenneth O. Stanley
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #36
Learning Implicitly Recurrent CNNs Through Parameter Sharing
Pedro Henrique Pamplona Savarese · Michael Maire
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #37
Identifying and Controlling Important Neurons in Neural Machine Translation
David A Bau · Yonatan Belinkov · Hassan Sajjad · Nadir Durrani · Fahim Dalvi · James R Glass
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #38
Learning Finite State Representations of Recurrent Policy Networks
Anurag Koul · Alan Fern · Samuel Greydanus
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #39
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Bo Chang · Minmin Chen · Eldad Haber · Ed H. Chi
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #40
Learning protein sequence embeddings using information from structure
Tristan Bepler · Bonnie Berger
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #41
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
Chih-Kuan Yeh · Jianshu Chen · Chengzhu Yu · Dong Yu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #42
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
Sachin Kumar · Yulia Tsvetkov
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #43
Transfer Learning for Sequences via Learning to Collocate
Wanyun Cui · Guangyu Zheng · Zhiqiang Shen · Sihang Jiang · Wei Wang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #44
Hyperbolic Attention Networks
Caglar Gulcehre · Misha Denil · Mateusz Malinowski · Ali Razavi · Razvan Pascanu · Karl Moritz Hermann · Victor Bapst · Victor Bapst · Adam Santoro · Nando de Freitas
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #45
Hierarchical interpretations for neural network predictions
Chandan Singh · William Murdoch · Bin Yu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #46
Hierarchical Generative Modeling for Controllable Speech Synthesis
Wei-Ning Hsu · Yu Zhang · Ron Weiss · Heiga Zen · Yonghui Wu · Yuxuan Wang · Yuan Cao · Ye Jia · Zhifeng Chen · Jonathan Shen · Patrick Nguyen · Ruoming Pang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #47
Learning what and where to attend
Drew Linsley · Dan Shiebler · Sven Eberhardt · Thomas Serre
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #48
Discovery of Natural Language Concepts in Individual Units of CNNs
Seil Na · Yo Joong Choe · Dong-Hyun Lee · Gunhee Kim
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #49
Posterior Attention Models for Sequence to Sequence Learning
Shiv Shankar · Sunita Sarawagi
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #50
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Vitalii Zhelezniak · Aleksandar D Savkov · April Shen · Francesco Moramarco · Jack Flann · Nils Hammerla
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #51
Learning to Represent Edits
Pengcheng Yin · Graham Neubig · Miltiadis Allamanis · Marc Brockschmidt · Alexander Gaunt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #52
What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney · Patrick Xia · Berlin Chen · Alex Wang · Adam Poliak · Tom McCoy · Najoung Kim · Benjamin Van Durme · Samuel R. Bowman · Dipanjan Das · Ellie Pavlick
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #53
Music Transformer: Generating Music with Long-Term Structure
Anna Huang · Ashish Vaswani · Jakob Uszkoreit · Ian Simon · Curtis Hawthorne · Noam Shazeer · Andrew Dai · Matthew D Hoffman · Monica Dinculescu · Douglas Eck
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #54
Representation Degeneration Problem in Training Natural Language Generation Models
Jun Gao · Di He · Xu Tan · Tao Qin · Liwei Wang · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #55
Detecting Egregious Responses in Neural Sequence-to-sequence Models
Tianxing He · James R Glass
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #56
Learning to Design RNA
Frederic Runge · Danny Stoll · Stefan Falkner · Frank Hutter
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #57
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
Xiaoshuai Zhang · Yiping Lu · Jiaying Liu · Bin Dong
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #58
Imposing Category Trees Onto Word-Embeddings Using A Geometric Construction
Tiansi Dong · Christian Bauckhage · Hailong Jin · Juanzi Li · Olaf Cremers · Daniel Speicher · Armin Cremers · Joerg Zimmermann
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #59
Multi-Agent Dual Learning
Yiren Wang · Yingce Xia · Tianyu He · Fei Tian · Tao Qin · ChengXiang Zhai · Tie-Yan Liu
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #61
Trellis Networks for Sequence Modeling
Shaojie Bai · Zico Kolter · Vladlen Koltun
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #62
Universal Transformers
Mostafa Dehghani · Stephan Gouws · Oriol Vinyals · Jakob Uszkoreit · Lukasz Kaiser
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #63
Structured Neural Summarization
Patrick Fernandes · Miltiadis Allamanis · Marc Brockschmidt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #64
Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
Chien-Sheng Wu · richard socher · Caiming Xiong
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #65
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following
Justin Fu · Anoop Korattikara Balan · Sergey Levine · Sergio Guadarrama
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #66
A Universal Music Translation Network
Noam Mor · Lior Wolf · Adam Polyak · Yaniv Taigman
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #67
Guiding Policies with Language via Meta-Learning
John Co-Reyes · Abhishek Gupta · Suvansh Sanjeev · Nicholas Altieri · Jacob Andreas · John DeNero · Pieter Abbeel · Sergey Levine
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #68
Recurrent Experience Replay in Distributed Reinforcement Learning
Steven Kapturowski · Georg Ostrovski · John Quan · Remi Munos · Will Dabney
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #69
Learning Multimodal Graph-to-Graph Translation for Molecule Optimization
Wengong Jin · Kevin Yang · Regina Barzilay · Tommi Jaakkola
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #70
Stable Recurrent Models
John Miller · Moritz Hardt
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #71
DARTS: Differentiable Architecture Search
Hanxiao Liu · Karen Simonyan · Yiming Yang
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #72
Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu · Angela Fan · Alexei Baevski · Yann Dauphin · Michael Auli
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #73
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang · Amanpreet Singh · Julian Michael · Felix Hill · Omer Levy · Samuel R. Bowman
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #74
Quaternion Recurrent Neural Networks
Titouan Parcollet · Mirco Ravanellu · Mohamed Morchid · Georges Linarès · Chiheb Trabelsi · Renato De Mori · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #76
Neural TTS Stylization with Adversarial and Collaborative Games
shuang ma · Daniel McDuff · Yale Song
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #77
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
Xiaodong Gu · Kyunghyun Cho · Jung-Woo Ha · Sunghun Kim
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #78
Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency
Liqian Ma · Xu Jia · Stamatios Georgoulis · Tinne Tuytelaars · Luc Gool
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #79
Improving Sequence-to-Sequence Learning via Optimal Transport
Liqun Chen · Yizhe Zhang · Ruiyi Zhang · Chenyang Tao · Zhe Gan · Haichao Zhang · Bai Li · Dinghan Shen · Changyou Chen · Lawrence Carin
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #80
A Max-Affine Spline Perspective of Recurrent Neural Networks
Richard Baraniuk · Jack Wang · Randall Balestriero
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #81
No Training Required: Exploring Random Encoders for Sentence Classification
John Wieting · Douwe Kiela
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #82
Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control
Róbert Csordás · Jürgen Schmidhuber
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #83
TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer
Sicong(Sheldon) Huang · Qiyang Li · Cem Anil · Xuchan Bao · Sageev Oore · Roger Grosse
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #84
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks
Patrick CHen · Si Si · Sanjiv Kumar · Yang Li · Cho-Jui Hsieh
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #85
Learning to Understand Goal Specifications by Modelling Reward
Felix Hill · Jan Leike · Edward Hughes · Arian Hosseini · Pushmeet Kohli · Edward Grefenstette · Dzmitry Bahdanau
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #86
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Maxime Chevalier-Boisvert · Dzmitry Bahdanau · Salem Lahlou · Lucas Willems · Chitwan Saharia · Thien H Nguyen · Yoshua Bengio
Poster
Thu May 9th 11:00 AM -- 01:00 PM @ Great Hall BC #87
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning
Anusha Nagabandi · Ignasi Clavera · Simin Liu · Ronald Fearing · Pieter Abbeel · Sergey Levine · Chelsea Finn
Break
Thu May 9th 01:00 -- 02:30 PM @ on your own
Lunch - on your own
Invited Talk
Thu May 9th 02:30 -- 03:15 PM @ Great Hall AD
Learning (from) language in context
Noah Goodman
Oral
Thu May 9th 03:15 -- 03:30 PM @ Great Hall AD
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz · Niru Maheswaranathan · Brian Cheung · Jascha Sohl-Dickstein
Oral
Thu May 9th 03:30 -- 03:45 PM @ Great Hall AD
Temporal Difference Variational Auto-Encoder
Karol Gregor · George Papamakarios · Frederic Besse · Lars Buesing · Theophane Weber
Oral
Thu May 9th 03:45 -- 04:00 PM @ Great Hall AD
Transferring Knowledge across Learning Processes
Sebastian Flennerhag · Pablo Moreno · Neil D Lawrence · Andreas Damianou
Break
Thu May 9th 04:00 -- 04:30 PM @ Hall B-1
Coffee Break
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #1
Stable Opponent Shaping in Differentiable Games
Alistair Letcher · Jakob N Foerster · David Balduzzi · Tim Rocktaeschel · Shimon Whiteson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #2
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He · Daniel Spokoyny · Graham Neubig · Taylor Berg-Kirkpatrick
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #3
Preventing Posterior Collapse with delta-VAEs
Ali Razavi · Aaron van den Oord · Ben Poole · Oriol Vinyals
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #4
Spectral Inference Networks: Unifying Deep and Spectral Learning
David Pfau · Stig Petersen · Ashish Agarwal · David GT Barrett · Kimberly L Stachenfeld
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #5
Learning Programmatically Structured Representations with Perceptor Gradients
Svetlin Penkov · Subramanian Ramamoorthy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #6
Variational Bayesian Phylogenetic Inference
Cheng Zhang · Frederick A Matsen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #7
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone · Jakob Kruse · Carsten Rother · Ullrich Koethe
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #8
Learning Representations of Sets through Optimized Permutations
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #9
Stochastic Prediction of Multi-Agent Interactions from Partial Observations
Chen Sun · Per Karlsson · Jiajun Wu · Joshua B Tenenbaum · Kevin Murphy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #10
Distribution-Interpolation Trade off in Generative Models
Damian Leśniak · Igor Sieradzki · Igor Podolak
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #11
Diagnosing and Enhancing VAE Models
Bin Dai · David Wipf
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #12
Generative Question Answering: Learning to Answer the Whole Question
Mike Lewis · Angela Fan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #13
Interpolation-Prediction Networks for Irregularly Sampled Time Series
Satya Narayan Shukla · Benjamin M Marlin
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #14
FUNCTIONAL VARIATIONAL BAYESIAN NEURAL NETWORKS
Shengyang Sun · Guodong Zhang · Jiaxin Shi · Roger Grosse
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #15
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks
Mingzhang Yin · Mingyuan Zhou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #16
Integer Networks for Data Compression with Latent-Variable Models
Johannes Ballé · Nick Johnston · David Minnen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #17
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models
Eirikur Agustsson · Alexander Sage · Radu Timofte · Luc S.J Van Gool
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #18
MARGINALIZED AVERAGE ATTENTIONAL NETWORK FOR WEAKLY-SUPERVISED LEARNING
Yuan Yuan · YUEMING LYU · Xi SHEN · Ivor Wai-Hung Tsang · Dit-Yan Yeung
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #19
Deep, Skinny Neural Networks are not Universal Approximators
Jesse Johnson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #20
Function Space Particle Optimization for Bayesian Neural Networks
Ziyu Wang · Tongzheng Ren · Jun Zhu · Bo Zhang
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #21
Measuring Compositionality in Representation Learning
Jacob Andreas
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #22
Variational Autoencoders with Jointly Optimized Latent Dependency Structure
Jiawei He · Yu Gong · Joe Marino · Greg Mori · Andreas Lehrmann
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #23
Learning Factorized Multimodal Representations
Yao Hung Tsai · Paul Pu Liang · Amir Ali Bagherzade · Louis-Philippe Morency · Ruslan Salakhutdinov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #24
On the loss landscape of a class of deep neural networks with no bad local valleys
Quynh Nguyen · Mahesh Chandra Mukkamala · Matthias Hein
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #25
Attentive Neural Processes
Hyunjik Kim · Andriy Mnih · Jonathan Schwarz · Marta Garnelo · S. M. Ali Eslami · Dan Rosenbaum · Oriol Vinyals · Yee Whye Teh
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #26
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
Wei Ping · Kainan Peng · Jitong Chen
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #27
Label super-resolution networks
Nikolay Malkin · Caleb Robinson · Le Hou · Rachel Soobitsky · Jacob Czawlytko · Dimitris Samaras · Joel Saltz · Lucas Joppa · Nebojsa Jojic
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #28
Learning from Positive and Unlabeled Data with a Selection Bias
Masahiro Kato · Takeshi Teshima · Junya Honda
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #29
Transferring Knowledge across Learning Processes
Sebastian Flennerhag · Pablo Moreno · Neil D Lawrence · Andreas Damianou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #30
Deep learning generalizes because the parameter-function map is biased towards simple functions
Guillermo Valle-Perez · Chico Q. Camargo · Ard Louis
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #31
Temporal Difference Variational Auto-Encoder
Karol Gregor · George Papamakarios · Frederic Besse · Lars Buesing · Theophane Weber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #32
Practical lossless compression with latent variables using bits back coding
James Townsend · Thomas Bird · David Barber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #33
Unsupervised Control Through Non-Parametric Discriminative Rewards
David Warde-Farley · Tom Wiele · Tejas Kulkarni · Catalin Ionescu · Steven S Hansen · Volodymyr Mnih
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #34
Information Theoretic lower bounds on negative log likelihood
Luis Lastras
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #35
Unsupervised Domain Adaptation for Distance Metric Learning
Kihyuk Sohn · Wenling Shang · Xiang Yu · Manmohan Chandraker
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #36
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Ryan L Murphy · Balasubramaniam Srinivasan · Vinayak Rao · Bruno Ribeiro
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #37
Learning Neural PDE Solvers with Convergence Guarantees
Jun-Ting Hsieh · Shengjia Zhao · Stephan Eismann · Lucia Mirabella · Stefano Ermon
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #38
How Important is a Neuron
Kedar Dhamdhere · Mukund Sundararajan · Qiqi Yan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #39
Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure
Karan Goel · Emma Brunskill
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #40
Auxiliary Variational MCMC
Raza Habib · David Barber
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #41
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian A. Rieck · Matteo Togninalli · Christian Bock · Michael Moor · Max Horn · Thomas Gumbsch · Karsten Borgwardt
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #42
Learning-Based Frequency Estimation Algorithms
Chen-Yu Hsu · Piotr Indyk · Dina Katabi · Ali Vakilian
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #43
Generative predecessor models for sample-efficient imitation learning
Yannick Schroecker · Mel Vecerik · Jon Scholz
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #44
Efficient Augmentation via Data Subsampling
Michael Kuchnik · Virginia Smith
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #45
LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION
Mahsa Baktashmotlagh · Masoud Faraki · Tom Drummond · Mathieu Salzmann
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #46
Sliced Wasserstein Auto-Encoders
Soheil Kolouri · Phillip Pope · Charles Martin · Gustavo Rohde
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #47
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection
Tue Le · Tuan Nguyen · Trung Le · Dinh Phung · Paul Montague · Olivier Vel · Lizhen Qu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #48
The Deep Weight Prior
Andrei Atanov · Arsenii Ashukha · Kirill Struminsky · Dmitry P. Vetrov · Max Welling
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #49
Feature-Wise Bias Amplification
Klas Leino · Matt Fredrikson · Emily Black · Shayak Sen · Anupam Datta
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #50
Generating Liquid Simulations with Deformation-aware Neural Networks
Lukas Prantl · Boris Bonev · Nils Thuerey
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #51
Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion
Ruiqi Gao · Jianwen Xie · Song-Chun Zhu · Yingnian Wu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #52
Toward Understanding the Impact of Staleness in Distributed Machine Learning
Wei Dai · Yi Zhou · Nanqing Dong · Hao Zhang · Eric Xing
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #53
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models
Marc T Law · Jake Snell · Amir-massoud Farahmand · Raquel Urtasun · Richard Zemel
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #54
GamePad: A Learning Environment for Theorem Proving
Daniel Huang · Prafulla Dhariwal · Dawn Song · Ilya Sutskever
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #55
Active Learning with Partial Feedback
Peiyun Hu · Zachary Lipton · Anima Anandkumar · Deva Ramanan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #56
On the Turing Completeness of Modern Neural Network Architectures
Jorge Pérez · Javier Marinković · Pablo Barceló
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #57
Learning a Meta-Solver for Syntax-Guided Program Synthesis
Xujie Si · Yuan Yang · Hanjun Dai · Mayur Naik · Le Song
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #58
DHER: Hindsight Experience Replay for Dynamic Goals
Meng Fang · Cheng Zhou · Bei Shi · Boqing Gong · Jia Xu · Tong Zhang
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #59
Spreading vectors for similarity search
Alexandre Sablayrolles · Matthijs Douze · Cordelia Schmid · Hervé Jégou
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #60
Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers
Alexander (Oleksandr) Shekhovtsov · Boris Flach
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #61
Kernel Change-point Detection with Auxiliary Deep Generative Models
Wei-Cheng Chang · Chun-Liang Li · Yiming Yang · Barnabás Póczos
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #62
Do Deep Generative Models Know What They Don't Know?
Eric Nalisnick · Akihiro Matsukawa · Yee Whye Teh · Dilan Gorur · Balaji Lakshminarayanan
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #63
Unsupervised Learning of the Set of Local Maxima
Lior Wolf · Sagie Benaim · Tomer Galanti
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #64
Modeling Uncertainty with Hedged Instance Embeddings
Seong Joon Oh · Andrew Gallagher · Kevin Murphy · Florian Schroff · Jiyan Pan · Joseph Roth
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #65
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman · Guy Uziel · Ran El-Yaniv
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #66
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
Yunzhu Li · Jiajun Wu · Russ Tedrake · Joshua B Tenenbaum · Antonio Torralba
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #67
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
George Tucker · Dieterich Lawson · Shixiang Gu · Chris J Maddison
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #68
Attention, Learn to Solve Routing Problems!
Wouter Kool · Herke van Hoof · Max Welling
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #69
Amortized Bayesian Meta-Learning
Sachin Ravi · Alex Beatson
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #70
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz · Niru Maheswaranathan · Brian Cheung · Jascha Sohl-Dickstein
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #71
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Xuezhe Ma · Chunting Zhou · Eduard Hovy
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #72
Variance Networks: When Expectation Does Not Meet Your Expectations
Kirill Neklyudov · Dmitry Molchanov · Arsenii Ashukha · Dmitry P. Vetrov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #73
Wasserstein Barycenter Model Ensembling
Pierre Dognin · Igor Melnyk · Youssef Mroueh · Jarret Ross · Cicero Nogueira dos Santos · Tom Sercu
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #74
Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov · Mikhail Figurnov · Dmitry P. Vetrov
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #75
Beyond Greedy Ranking: Slate Optimization via List-CVAE
Ray Jiang · Sven Gowal · Yuqiu Qian · Timothy A Mann · Danilo J Rezende
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #76
Bayesian Policy Optimization for Model Uncertainty
Gilwoo Lee · Brian Hou · Aditya Mandalika · Jeongseok Lee · Sanjiban Choudhury · Siddhartha Srinivasa
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #77
Efficiently testing local optimality and escaping saddles for ReLU networks
Chulhee Yun · Suvrit Sra · Ali Jadbabaie
Poster
Thu May 9th 04:30 -- 06:30 PM @ Great Hall BC #78
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Charbel Sakr · Naigang Wang · Chia-Yu Chen · Jungwook Choi · Ankur Agrawal · Naresh Shanbhag · Kailash Gopalakrishnan
Break
Thu May 9th 06:30 -- 08:30 PM @ Great Hall Pre-Function, Hall B-1
Closing Reception