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Poster
Mon 2:30 DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
Wenqian Li · Yinchuan Li · Zhigang Li · Jianye HAO · Yan Pang
Poster
Mon 7:30 Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics
Taiji Suzuki · Atsushi Nitanda · Denny Wu
Poster
Wed 7:30 Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods
Akiyama Shunta · Taiji Suzuki
Poster
Wed 2:30 Confidence-Based Feature Imputation for Graphs with Partially Known Features
Daeho Um · Jiwoong Park · Seulki Park · Jin Choi
Workshop
Tue 2:30 How does the inductive bias influence the generalization capability of neural networks?
Charlotte Barth · Thomas Goerttler · Klaus Obermayer
Workshop
Fri 2:25 Spotlight: Ten Lessons We Have Learned in the New ''Sparseland'': A Short Handbook for Sparse Neural Network Researchers
Shiwei Liu · Zhangyang Wang
Poster
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Difan Zou · Yuan Cao · Yuanzhi Li · Quanquan Gu
Poster
Reparameterization through Spatial Gradient Scaling
Alexander Detkov · Mohammad Salameh · Muhammad Fetrat Qharabagh · Jialin Zhang · Wei Lu · SHANGLING JUI · Di Niu
Poster
Tue 7:30 Modelling Long Range Dependencies in ND: From Task-Specific to a General Purpose CNN
David Knigge · David W. Romero · Albert Gu · Efstratios Gavves · Erik Bekkers · Jakub Tomczak · Mark Hoogendoorn · Jan-jakob Sonke
Poster
Implicit Regularization for Group Sparsity
Jiangyuan Li · THANH NGUYEN · Chinmay Hegde · Raymond K. W. Wong
Poster
What Makes Convolutional Models Great on Long Sequence Modeling?
Yuhong Li · Tianle Cai · Yi Zhang · Deming Chen · Debadeepta Dey
Poster
Pruning Deep Neural Networks from a Sparsity Perspective
Enmao Diao · Ganghua Wang · Jiawei Zhang · Yuhong Yang · Jie Ding · VAHID TAROKH