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07/03/2023
Quantum Neural Estimation of Entropies
Entropy measures quantify the amount of information and correlations pre...
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06/22/2023
Quantum Pufferfish Privacy: A Flexible Privacy Framework for Quantum Systems
We propose a versatile privacy framework for quantum systems, termed qua...
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05/31/2023
Entropic Gromov-Wasserstein Distances: Stability, Algorithms, and Distributional Limits
The Gromov-Wasserstein (GW) distance quantifies discrepancy between metr...
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03/17/2023
Limit theorems for semidiscrete optimal transport maps
We study statistical inference for the optimal transport (OT) map (also ...
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02/02/2023
Robust Estimation under the Wasserstein Distance
We study the problem of robust distribution estimation under the Wassers...
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01/02/2023
Data-Driven Optimization of Directed Information over Discrete Alphabets
Directed information (DI) is a fundamental measure for the study and ana...
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12/25/2022
Gromov-Wasserstein Distances: Entropic Regularization, Duality, and Sample Complexity
The Gromov-Wasserstein (GW) distance quantifies dissimilarity between me...
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11/21/2022
Limit distribution theory for f-Divergences
f-divergences, which quantify discrepancy between probability distributi...
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10/23/2022
Pufferfish Privacy: An Information-Theoretic Study
Pufferfish privacy (PP) is a generalization of differential privacy (DP)...
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10/17/2022
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
Sliced Wasserstein distances preserve properties of classic Wasserstein ...
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07/18/2022
Limit Theorems for Entropic Optimal Transport Maps and the Sinkhorn Divergence
We study limit theorems for entropic optimal transport (EOT) maps, dual ...
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06/17/2022
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension
Sliced mutual information (SMI) is defined as an average of mutual infor...
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05/09/2022
Statistical inference with regularized optimal transport
Optimal transport (OT) is a versatile framework for comparing probabilit...
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03/28/2022
Neural Estimation and Optimization of Directed Information over Continuous Spaces
This work develops a new method for estimating and optimizing the direct...
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03/01/2022
Limit distribution theory for smooth p-Wasserstein distances
The Wasserstein distance is a metric on a space of probability measures ...
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11/22/2021
Cycle Consistent Probability Divergences Across Different Spaces
Discrepancy measures between probability distributions are at the core o...
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11/02/2021
Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
The Wasserstein distance, rooted in optimal transport (OT) theory, is a ...
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10/11/2021
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Mutual information (MI) is a fundamental measure of statistical dependen...
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10/07/2021
Neural Estimation of Statistical Divergences
Statistical divergences (SDs), which quantify the dissimilarity between ...
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07/28/2021
Limit Distribution Theory for the Smooth 1-Wasserstein Distance with Applications
The smooth 1-Wasserstein distance (SWD) W_1^σ was recently proposed as a...
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03/11/2021
Non-Asymptotic Performance Guarantees for Neural Estimation of 𝖿-Divergences
Statistical distances (SDs), which quantify the dissimilarity between pr...
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01/11/2021
From Smooth Wasserstein Distance to Dual Sobolev Norm: Empirical Approximation and Statistical Applications
Statistical distances, i.e., discrepancy measures between probability di...
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04/30/2020
The Information Bottleneck Problem and Its Applications in Machine Learning
Inference capabilities of machine learning (ML) systems skyrocketed in r...
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04/09/2020
The Secrecy Capacity of Cost-Constrained Wiretap Channels
In many information-theoretic communication problems, adding an input co...
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03/09/2020
Capacity of Continuous Channels with Memory via Directed Information Neural Estimator
Calculating the capacity (with or without feedback) of channels with mem...
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02/03/2020
Limit Distribution for Smooth Total Variation and χ^2-Divergence in High Dimensions
Statistical divergences are ubiquitous in machine learning as tools for ...
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02/03/2020
Limit Distribution Theory for Smooth Wasserstein Distance with Applications to Generative Modeling
The 1-Wasserstein distance (W_1) is a popular proximity measure between ...
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01/24/2020
Gaussian-Smooth Optimal Transport: Metric Structure and Statistical Efficiency
Optimal transport (OT), and in particular the Wasserstein distance, has ...
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05/30/2019
Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation
This paper studies convergence of empirical measures smoothed by a Gauss...
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10/27/2018
Estimating Differential Entropy under Gaussian Convolutions
This paper studies the problem of estimating the differential entropy h(...
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10/12/2018
Estimating Information Flow in Neural Networks
We study the flow of information and the evolution of internal represent...
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05/08/2018
Information Storage in the Stochastic Ising Model
Most information systems store data by modifying the local state of matt...
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12/29/2017