Frederic Koehler
25 papers · 2016–2025 · 4 conferences · across top CS/AI conferences
Achievements
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🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (4) 🏃 Academic Marathon (9) 🐝 Cross-Pollinator (10) 🌉 Interdisciplinary Bridge
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Conference Polyglot
(4)
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Academic Marathon
(9)
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(5)
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Century Club
(25)
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Prolific Year
(5)
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(10)
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Keyword Collector
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Conferences
NIPS (11)
COLT (6)
ICLR (4)
ICML (4)
Top co-authors
Keywords
ising model
(5)
sparse linear regression
(4)
markov random field
(3)
graphical model
(3)
belief propagation
(3)
variational inference
(2)
interpolation learning
(2)
markov chain monte carlo
(2)
phase transition
(2)
latent variable model
(2)
gaussian graphical model
(2)
uniform convergence
(2)
generalization bound
(2)
high-dimensional statistics
(2)
generalized linear model
(2)
theoretical analysis
(1)
sample complexity
(1)
mean field approximation
(1)
stochastic gradient descent
(1)
dimensionality reduction
(1)
Papers
Efficiently learning and sampling multimodal distributions with data-based initialization
COLT 2025
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
ICML 2024
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
ICLR 2024
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps
COLT 2024
Feature Adaptation for Sparse Linear Regression
NIPS 2023
Uniform Convergence with Square-Root Lipschitz Loss
NIPS 2023
Statistical Efficiency of Score Matching: The View from Isoperimetry
ICLR 2023
Reconstruction on Trees and Low-Degree Polynomials
NIPS 2022
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs
NIPS 2022
Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods
COLT 2022
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias
ICLR 2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
NIPS 2022
Representational aspects of depth and conditioning in normalizing flows
ICML 2021
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting
NIPS 2021
Multidimensional Scaling: Approximation and Complexity
ICML 2021
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
NIPS 2020
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability
NIPS 2020
From Boltzmann Machines to Neural Networks and Back Again
NIPS 2020
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure
ICLR 2019
Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation
COLT 2019
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay
NIPS 2019
The Vertex Sample Complexity of Free Energy is Polynomial
COLT 2018
The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity
COLT 2018
Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications
NIPS 2017
Provable Algorithms for Inference in Topic Models
ICML 2016