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04/27/2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers
Annealed Importance Sampling (AIS) moves particles along a Markov chain ...
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02/09/2023
Trading Information between Latents in Hierarchical Variational Autoencoders
Variational Autoencoders (VAEs) were originally motivated (Kingma We...
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02/17/2022
Hybridizing Physical and Data-driven Prediction Methods for Physicochemical Properties
We present a generic way to hybridize physical and data-driven methods f...
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01/05/2022
Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective
Entropy coding is the backbone data compression. Novel machine-learning ...
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11/06/2020
User-Dependent Neural Sequence Models for Continuous-Time Event Data
Continuous-time event data are common in applications such as individual...
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06/07/2020
Improving Inference for Neural Image Compression
We consider the problem of lossy image compression with deep latent vari...
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02/18/2020
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding
Deep Bayesian latent variable models have enabled new approaches to both...
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02/15/2020
Extreme Classification via Adversarial Softmax Approximation
Training a classifier over a large number of classes, known as 'extreme ...
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01/29/2020
Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion
Activity coefficients, which are a measure of the non-ideality of liquid...
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09/30/2019
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory
Variational inference has become one of the most widely used methods in ...
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07/04/2019
A Quantum Field Theory of Representation Learning
Continuous symmetries and their breaking play a prominent role in contem...
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07/01/2019
Augmenting and Tuning Knowledge Graph Embeddings
Knowledge graph embeddings rank among the most successful methods for li...
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03/08/2018
Improving Optimization in Models With Continuous Symmetry Breaking
Many loss functions in representation learning are invariant under a con...
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11/10/2017
Bayesian Paragraph Vectors
Word2vec (Mikolov et al., 2013) has proven to be successful in natural l...
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09/21/2017
Perturbative Black Box Variational Inference
Black box variational inference (BBVI) with reparameterization gradients...
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07/04/2017
Structured Black Box Variational Inference for Latent Time Series Models
Continuous latent time series models are prevalent in Bayesian modeling;...
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02/27/2017
