Papers
Training Binary Neural Networks using the Bayesian Learning Rule
Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan
Training Deep Energy-Based Models with f-Divergence Minimization
Lantao Yu, Yang Song, Jiaming Song et al.
Training Neural Networks for and by Interpolation
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Alexander Tong, Jessie Huang, Guy Wolf et al.
Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time
Zahra Monfared, Daniel Durstewitz
Transformer Hawkes Process
Simiao Zuo, Haoming Jiang, Zichong Li et al.
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas et al.
Transparency Promotion with Model-Agnostic Linear Competitors
Hassan Rafique, Tong Wang, Qihang Lin et al.
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang et al.
Two Routes to Scalable Credit Assignment without Weight Symmetry
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena et al.
Two Simple Ways to Learn Individual Fairness Metrics from Data
Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee et al.
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin et al.
Uncertainty-Aware Lookahead Factor Models for Quantitative Investing
Lakshay Chauhan, John Alberg, Zachary Lipton
Uncertainty Estimation Using a Single Deep Deterministic Neural Network
Joost Van Amersfoort, Lewis Smith, Yee Whye Teh et al.
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai, H. Vincent Poor, Yuxin Chen
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
Aditi Raghunathan, Sang Michael Xie, Fanny Yang et al.
Understanding and Stabilizing GANs’ Training Dynamics Using Control Theory
Kun Xu, Chongxuan Li, Jun Zhu et al.
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang, Phillip Isola
Understanding Self-Training for Gradual Domain Adaptation
Ananya Kumar, Tengyu Ma, Percy Liang
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
Yao Liu, Pierre-Luc Bacon, Emma Brunskill
Undirected Graphical Models as Approximate Posteriors
Arash Vahdat, Evgeny Andriyash, William Macready
Uniform Convergence of Rank-weighted Learning
Justin Khim, Liu Leqi, Adarsh Prasad et al.