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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