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09/18/2023
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
Tabular data is hard to acquire and is subject to missing values. This p...
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04/12/2023
Diffusion models with location-scale noise
Diffusion Models (DMs) are powerful generative models that add Gaussian ...
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04/06/2023
PopulAtion Parameter Averaging (PAPA)
Ensemble methods combine the predictions of multiple models to improve p...
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10/18/2022
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback
We propose a novel regularizer for supervised learning called Conditioni...
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05/19/2022
Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Video prediction is a challenging task. The quality of video frames from...
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05/28/2021
Gotta Go Fast When Generating Data with Score-Based Models
Score-based (denoising diffusion) generative models have recently gained...
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09/11/2020
Adversarial score matching and improved sampling for image generation
Denoising score matching with Annealed Langevin Sampling (DSM-ALS) is a ...
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07/08/2020
Stochastic Hamiltonian Gradient Methods for Smooth Games
The success of adversarial formulations in machine learning has brought ...
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10/15/2019
Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs
We generalize the concept of maximum-margin classifiers (MMCs) to arbitr...
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01/08/2019
On Relativistic f-Divergences
This paper provides a more rigorous look at Relativistic Generative Adve...
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09/06/2018
GANs beyond divergence minimization
Generative adversarial networks (GANs) can be interpreted as an adversar...
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07/02/2018
The relativistic discriminator: a key element missing from standard GAN
In standard generative adversarial network (SGAN), the discriminator est...
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12/11/2017