Papers
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan et al.
Understanding Noise Injection in GANs
Ruili Feng, Deli Zhao, Zheng-Jun Zha
Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin D Haeffele et al.
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng et al.
UnICORNN: A recurrent model for learning very long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann
Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan et al.
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian et al.
Unitary Branching Programs: Learnability and Lower Bounds
Fidel Ernesto Diaz Andino, Maria Kokkou, Mateus De Oliveira Oliveira et al.
Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu et al.
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Hoon Lee, Sae-Young Chung
Unsupervised Learning of Visual 3D Keypoints for Control
Boyuan Chen, Pieter Abbeel, Deepak Pathak
Unsupervised Part Representation by Flow Capsules
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani et al.
Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim et al.
Unsupervised Skill Discovery with Bottleneck Option Learning
Jaekyeom Kim, Seohong Park, Gunhee Kim
Valid Causal Inference with (Some) Invalid Instruments
Jason S Hartford, Victor Veitch, Dhanya Sridhar et al.
Value Alignment Verification
Daniel S Brown, Jordan Schneider, Anca Dragan et al.
Value-at-Risk Optimization with Gaussian Processes
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low et al.
Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters et al.
Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen et al.
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
Chaobing Song, Stephen J Wright, Jelena Diakonikolas