20 citations · 57 across the 7 of their papers we have counts for
7 papers
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
David Berthelot, Arnaud Autef, Jierui Lin +6
Denoising Diffusion models have demonstrated their proficiency for generative sampling. However, generating good samples often requires many iterations. Consequently, techniques su…
BERT Learns (and Teaches) Chemistry
Josh Payne, Mario Srouji, Dian Ang Yap +1
Modern computational organic chemistry is becoming increasingly data-driven. There remain a large number of important unsolved problems in this area such as product prediction give…
Deep Connectomics Networks: Neural Network Architectures Inspired by Neuronal Networks
Nicholas Roberts, Dian Ang Yap, Vinay Uday Prabhu
The interplay between inter-neuronal network topology and cognition has been studied deeply by connectomics researchers and network scientists, which is crucial towards understandi…
Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity
Dian Ang Yap, Nicholas Roberts, Vinay Uday Prabhu
Kernel sparsity ("dying ReLUs") and lack of diversity are commonly observed in CNN kernels, which decreases model capacity. Drawing inspiration from information theory and wireless…
Covering up bias in CelebA-like datasets with Markov blankets: A post-hoc cure for attribute prior avoidance
Vinay Uday Prabhu, Dian Ang Yap, Alexander Wang +1
Attribute prior avoidance entails subconscious or willful non-modeling of (meta)attributes that datasets are oft born with, such as the 40 semantic facial attributes associated wit…
Understanding Adversarial Robustness Through Loss Landscape Geometries
Vinay Uday Prabhu, Dian Ang Yap, Joyce Xu +1
The pursuit of explaining and improving generalization in deep learning has elicited efforts both in regularization techniques as well as visualization techniques of the loss surfa…
Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification
Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap +3
In this paper, we propose a Seed-Augment-Train/Transfer (SAT) framework that contains a synthetic seed image dataset generation procedure for languages with different numeral syste…