Papers
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Derek Yang, Li Zhao, Zichuan Lin et al.
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks
Wenrui Zhang, Peng Li
Generative Models for Graph-Based Protein Design
John Ingraham, Vikas Garg, Regina Barzilay et al.
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks
Gauthier Gidel, Francis Bach, Simon Lacoste-Julien
Deep Learning without Weight Transport
Mohamed Akrout, Collin Wilson, Peter Humphreys et al.
Quantum Wasserstein Generative Adversarial Networks
Shouvanik Chakrabarti, Huang Yiming, Tongyang Li et al.
Thompson Sampling and Approximate Inference
My Phan, Yasin Abbasi Yadkori, Justin Domke
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
Xiaohan Ding, guiguang ding, Xiangxin Zhou et al.
Nonzero-sum Adversarial Hypothesis Testing Games
Sarath Yasodharan, Patrick Loiseau
DppNet: Approximating Determinantal Point Processes with Deep Networks
Zelda E. Mariet, Yaniv Ovadia, Jasper Snoek
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning
Igor Colin, Ludovic DOS SANTOS, Kevin Scaman
Neural Attribution for Semantic Bug-Localization in Student Programs
Rahul Gupta, Aditya Kanade, Shirish Shevade
Towards a Zero-One Law for Column Subset Selection
Zhao Song, David Woodruff, Peilin Zhong
CondConv: Conditionally Parameterized Convolutions for Efficient Inference
Brandon Yang, Gabriel Bender, Quoc V Le et al.
Deep Generative Video Compression
Salvator Lombardo, JUN HAN, Christopher Schroers et al.
A General Framework for Symmetric Property Estimation
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
When does label smoothing help?
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
Prior-Free Dynamic Auctions with Low Regret Buyers
Yuan Deng, Jon Schneider, Balasubramanian Sivan
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Cole Hurwitz, Kai Xu, Akash Srivastava et al.
Outlier-robust estimation of a sparse linear model using ℓ_1-penalized Huber's M-estimator
Arnak Dalalyan, Philip Thompson
Generalized Sliced Wasserstein Distances
Soheil Kolouri, Kimia Nadjahi, Umut Simsekli et al.
Differentially Private Anonymized Histograms
Ananda Theertha Suresh
Deep Scale-spaces: Equivariance Over Scale
Daniel Worrall, Max Welling
Abstract Reasoning with Distracting Features
Kecheng Zheng, Zheng-Jun Zha, Wei Wei
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan et al.