67 citations · 80 across the 4 of their papers we have counts for
5 papers
Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg +4
Autoregressive models are widely used for tasks such as image and audio generation. The sampling process of these models, however, does not allow interruptions and cannot adapt to…
Confounding Tradeoffs for Neural Network Quantization
Sahaj Garg, Anirudh Jain, Joe Lou +1
Many neural network quantization techniques have been developed to decrease the computational and memory footprint of deep learning. However, these methods are evaluated subject to…
Dynamic Precision Analog Computing for Neural Networks
Sahaj Garg, Joe Lou, Anirudh Jain +1
Analog electronic and optical computing exhibit tremendous advantages over digital computing for accelerating deep learning when operations are executed at low precision. In this w…
Sliced Score Matching: A Scalable Approach to Density and Score Estimation
Yang Song, Sahaj Garg, Jiaxin Shi +1
Score matching is a popular method for estimating unnormalized statistical models. However, it has been so far limited to simple, shallow models or low-dimensional data, due to the…
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco +3
In this paper, we study counterfactual fairness in text classification, which asks the question: How would the prediction change if the sensitive attribute referenced in the exampl…