When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
- Lijie Fan
- Sijia Liu
- et al.
- 2021
- NeurIPS 2021
Publications
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs
- Michael Boratko
- Dongxu Zhang
- et al.
- 2021
- NeurIPS 2021
Cardinality-Regularized Hawkes-Granger Model
- Ide-San Ide
- Georgios Kollias
- et al.
- 2021
- NeurIPS 2021
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations
- Yu-Lin Tsai
- Chia-Yi Hsu
- et al.
- 2021
- NeurIPS 2021
IA-RED^2 : Interpretability-Aware Redundancy Reduction for Vision Transformers
- Bowen Pan
- Rameswar Panda
- et al.
- 2021
- NeurIPS 2021
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
- Kai Xu
- Akash Srivastava
- et al.
- 2021
- NeurIPS 2021
Measuring Generalization with Optimal Transport
- Ching-Yao Chuang
- Youssef Mroueh
- et al.
- 2021
- NeurIPS 2021
Private learning implies quantum stability
- Srinivasan Arunachalam
- Yihui Quek
- et al.
- 2021
- NeurIPS 2021
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
- Rong Zhu
- Mattia Rigotti
- 2021
- NeurIPS 2021
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization
- Kuniaki Saito
- Donghyun Kim
- et al.
- 2021
- NeurIPS 2021