Code for our AISTATS '22 paper: Improving Attribution Methods by Learning Submodular Functions.
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Updated
Nov 5, 2023 - Jupyter Notebook
Code for our AISTATS '22 paper: Improving Attribution Methods by Learning Submodular Functions.
PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).
Training Implicit Generative Models via an Invariant statistical loss (ISL)
AISTATS 2019: Lovász Convolutional Networks
Spectral Tensor Train Parameterization of Deep Learning Layers
DPE code - Code used in "Optimal Algorithms for Multiplayer Multi-Armed Bandits" (AISTATS 2020)
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
A near-optimal exact sampler for discrete probability distributions
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
For deep RL and the future of AI.
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