142 citations · 246 across the 7 of their papers we have counts for
3 papers · 1 filter
In-context Reinforcement Learning with Algorithm Distillation
Michael Laskin, Luyu Wang, Junhyuk Oh +11
We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL) algorithms into neural networks by modeling their training histories with a causal seque…
On the Sensitivity of Adversarial Robustness to Input Data Distributions
Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin +2
Neural networks are vulnerable to small adversarial perturbations. Existing literature largely focused on understanding and mitigating the vulnerability of learned models. In this…
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
Gavin Weiguang Ding, Luyu Wang, Xiaomeng Jin
advertorch is a toolbox for adversarial robustness research. It contains various implementations for attacks, defenses and robust training methods. advertorch is built on PyTorch (…