1.3k citations · 1.5k across the 16 of their papers we have counts for
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Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma +3
Creating noise from data is easy; creating data from noise is generative modeling. We present a stochastic differential equation (SDE) that smoothly transforms a complex data distr…
Few-Shot Adaptation of Generative Adversarial Networks
Esther Robb, Wen-Sheng Chu, Abhishek Kumar +1
Generative Adversarial Networks (GANs) have shown remarkable performance in image synthesis tasks, but typically require a large number of training samples to achieve high-quality…
Generalized Adversarially Learned Inference
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar +1
Allowing effective inference of latent vectors while training GANs can greatly increase their applicability in various downstream tasks. Recent approaches, such as ALI and BiGAN fr…
MCQA: Multimodal Co-attention Based Network for Question Answering
Abhishek Kumar, Trisha Mittal, Dinesh Manocha
We present MCQA, a learning-based algorithm for multimodal question answering. MCQA explicitly fuses and aligns the multimodal input (i.e. text, audio, and video), which forms the…
On Implicit Regularization in -VAEs
Abhishek Kumar, Ben Poole
While the impact of variational inference (VI) on posterior inference in a fixed generative model is well-characterized, its role in regularizing a learned generative model when us…