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02/01/2023
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics
Coarse-grained (CG) molecular dynamics enables the study of biological p...
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09/30/2022
Protein structure generation via folding diffusion
The ability to computationally generate novel yet physically foldable pr...
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09/08/2022
Clifford Neural Layers for PDE Modeling
Partial differential equations (PDEs) see widespread use in sciences and...
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10/05/2021
Autoregressive Diffusion Models
We introduce Autoregressive Diffusion Models (ARDMs), a model class enco...
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07/16/2021
Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models
Denoising diffusion probabilistic models (DDPMs) have shown impressive r...
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07/07/2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Denoising diffusion probabilistic models (DDPMs) (Ho et al. 2020) have s...
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06/10/2021
Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent
We focus on the problem of domain adaptation when the goal is shifting t...
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08/03/2020
A Spectral Energy Distance for Parallel Speech Synthesis
Speech synthesis is an important practical generative modeling problem t...
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06/22/2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
In this paper we analyse and improve integer discrete flows for lossless...
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06/18/2019
Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
Scientific imaging techniques such as optical and electron microscopy an...
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05/17/2019
Integer Discrete Flows and Lossless Compression
Lossless compression methods shorten the expected representation size of...
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01/30/2019
Emerging Convolutions for Generative Normalizing Flows
Generative flows are attractive because they admit exact likelihood opti...
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10/12/2018
Predictive Uncertainty through Quantization
High-risk domains require reliable confidence estimates from predictive ...
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10/02/2018
Sinkhorn AutoEncoders
Optimal Transport offers an alternative to maximum likelihood for learni...
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03/15/2018
Sylvester Normalizing Flows for Variational Inference
Variational inference relies on flexible approximate posterior distribut...
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06/07/2017
Graph Convolutional Matrix Completion
We consider matrix completion for recommender systems from the point of ...
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03/17/2017