Search Results for author: Siddhant Agarwal

Found 6 papers, 3 papers with code

$f$-Policy Gradients: A General Framework for Goal Conditioned RL using $f$-Divergences

no code implementations10 Oct 2023 Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang

We further introduce an entropy-regularized policy optimization objective, that we call $state$-MaxEnt RL (or $s$-MaxEnt RL) as a special case of our objective.

Efficient Exploration Policy Gradient Methods +1

Reinforcement Explanation Learning

no code implementations26 Nov 2021 Siddhant Agarwal, Owais Iqbal, Sree Aditya Buridi, Madda Manjusha, Abir Das

Black-box methods to generate saliency maps are particularly interesting due to the fact that they do not utilize the internals of the model to explain the decision.

Image Classification object-detection +2

Deep learning for surrogate modelling of 2D mantle convection

no code implementations23 Aug 2021 Siddhant Agarwal, Nicola Tosi, Pan Kessel, Doris Breuer, Grégoire Montavon

Using a dataset of 10, 525 two-dimensional simulations of the thermal evolution of the mantle of a Mars-like planet, we show that deep learning techniques can produce reliable parameterized surrogates (i. e. surrogates that predict state variables such as temperature based only on parameters) of the underlying partial differential equations.

Poisoned classifiers are not only backdoored, they are fundamentally broken

1 code implementation18 Oct 2020 MingJie Sun, Siddhant Agarwal, J. Zico Kolter

Under this threat model, we propose a test-time, human-in-the-loop attack method to generate multiple effective alternative triggers without access to the initial backdoor and the training data.

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