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07/03/2023
Transport, Variational Inference and Diffusions: with Applications to Annealed Flows and Schrödinger Bridges
This paper explores the connections between optimal transport and variat...
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05/16/2023
Expressiveness Remarks for Denoising Diffusion Models and Samplers
Denoising diffusion models are a class of generative models which have r...
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04/15/2023
Dimensionality Reduction as Probabilistic Inference
Dimensionality reduction (DR) algorithms compress high-dimensional data ...
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02/27/2023
Denoising Diffusion Samplers
Denoising diffusion models are a popular class of generative models prov...
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01/28/2022
Adversarial Concept Erasure in Kernel Space
The representation space of neural models for textual data emerges in an...
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11/20/2021
Bayesian Learning via Neural Schrödinger-Föllmer Flows
In this work we explore a new framework for approximate Bayesian inferen...
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10/15/2021
Efficient Representations for Privacy-Preserving Inference
Deep neural networks have a wide range of applications across multiple d...
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06/03/2021
Solving Schrödinger Bridges via Maximum Likelihood
The Schrödinger bridge problem (SBP) finds the most likely stochastic ev...
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09/20/2020
Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
Bolukbasi et al. (2016) presents one of the first gender bias mitigation...
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05/14/2019
Multilingual Factor Analysis
In this work we approach the task of learning multilingual word represen...
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04/30/2019
Model Comparison for Semantic Grouping
We introduce a probabilistic framework for quantifying the semantic simi...
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03/20/2016
Towards Automatic Wild Animal Monitoring: Identification of Animal Species in Camera-trap Images using Very Deep Convolutional Neural Networks
Non intrusive monitoring of animals in the wild is possible using camera...
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02/11/2016