Papers
11,951 papers found
Improving VAEs' Robustness to Adversarial Attack
Matthew JF Willetts, Alexander Camuto, Tom Rainforth et al.
Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning
Siyang Yuan, Pengyu Cheng, Ruiyi Zhang et al.
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Rui Wang, Robin Walters, Rose Yu
Incremental few-shot learning via vector quantization in deep embedded space
Kuilin Chen, Chi-Guhn Lee
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat et al.
Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin et al.
Individually Fair Rankings
Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin et al.
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu et al.
Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka et al.
Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Boxin Wang, Shuohang Wang, Yu Cheng et al.
Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao et al.
Initialization and Regularization of Factorized Neural Layers
Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey et al.
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones et al.
In Search of Lost Domain Generalization
Ishaan Gulrajani, David Lopez-Paz
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
Yuhuai Wu, Albert Jiang, Jimmy Ba et al.
Integrating Categorical Semantics into Unsupervised Domain Translation
Samuel Lavoie-Marchildon, Faruk Ahmed, Aaron Courville
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Benedikt Boecking, Willie Neiswanger, Eric Xing et al.
Interpretable Models for Granger Causality Using Self-explaining Neural Networks
Ričards Marcinkevičs, Julia E Vogt
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
Binxin Ru, Xingchen Wan, Xiaowen Dong et al.
Interpreting and Boosting Dropout from a Game-Theoretic View
Hao Zhang, Sen Li, YinChao Ma et al.
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov
Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balazevic, Timothy Hospedales
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
Efthymios Tzinis, Scott Wisdom, Aren Jansen et al.
Intraclass clustering: an implicit learning ability that regularizes DNNs
Simon Carbonnelle, Christophe De Vleeschouwer