Note On Mutual Information and Orthogonal Space-Time Codes. - Guy Bresler; Bruce E. Hajek (ISIT, 2006)

Reconstruction of Markov Random Fields from Samples: Some Easy Observations and Algorithms - Guy Bresler; Elchanan Mossel; Allan Sly (CoRR, 2007)

Mixing Time of Exponential Random Graphs. - Shankar Bhamidi; Guy Bresler; Allan Sly (FOCS, 2008)

The two-user Gaussian interference channel: a deterministic view. - Guy Bresler; David Tse (Eur. Trans. Telecommun., 2008)

3 User interference channel: Degrees of freedom as a function of channel diversity. - Guy Bresler; David N. C. Tse (Allerton, 2009)

The approximate capacity of the many-to-one and one-to-many Gaussian interference channels. - Guy Bresler; Abhay Parekh; David N. C. Tse (IEEE Trans. Inf. Theory, 2010)

Geometry of the 3-user MIMO interference channel. - Guy Bresler; Dustin Cartwright; David Tse (Allerton, 2011)

Feasibility of interference alignment for the MIMO interference channel: The symmetric square case. - Guy Bresler; Dustin Cartwright; David N. C. Tse (ITW, 2011)

Settling the feasibility of interference alignment for the MIMO interference channel: the symmetric square case - Guy Bresler; Dustin Cartwright; David Tse (CoRR, 2011)

Information theory for DNA sequencing: Part I: A basic model. - Abolfazl S. Motahari; Guy Bresler; David Tse (ISIT, 2012)

Information Theory of DNA Sequencing - Abolfazl S. Motahari; Guy Bresler; David Tse (CoRR, 2012)

Fundamental limits and insights: from wireless communication to DNA sequencing. - Guy Bresler (2012)

Optimal Assembly for High Throughput Shotgun Sequencing - Guy Bresler; Ma'ayan Bresler; David Tse (CoRR, 2013)

Interference alignment for the MIMO interference channel - Guy Bresler; Dustin Cartwright; David Tse (CoRR, 2013)

Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms. - Guy Bresler; Elchanan Mossel; Allan Sly (SIAM J. Comput., 2013)

Information Theory of DNA Shotgun Sequencing. - Abolfazl S. Motahari; Guy Bresler; David N. C. Tse (IEEE Trans. Inf. Theory, 2013)

A Latent Source Model for Online Collaborative Filtering. - Guy Bresler; George H. Chen; Devavrat Shah (NIPS, 2014)

Hardness of parameter estimation in graphical models. - Guy Bresler; David Gamarnik; Devavrat Shah (NIPS, 2014)

Structure learning of antiferromagnetic Ising models. - Guy Bresler; David Gamarnik; Devavrat Shah (NIPS, 2014)

Efficiently learning Ising models on high degree graphs. - Guy Bresler (CoRR, 2014)

Feasibility of Interference Alignment for the MIMO Interference Channel. - Guy Bresler; Dustin Cartwright; David Tse (IEEE Trans. Inf. Theory, 2014)

Inferning trees. - Mina Karzand; Guy Bresler (Allerton, 2015)

Efficiently Learning Ising Models on Arbitrary Graphs. - Guy Bresler (STOC, 2015)

Collaborative Filtering with Low Regret. - Guy Bresler; Devavrat Shah; Luis Filipe Voloch (SIGMETRICS, 2016)

Learning a Tree-Structured Ising Model in Order to Make Predictions. - Guy Bresler; Mina Karzand (CoRR, 2016)

Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure. - Matthew S. Brennan; Guy Bresler; Wasim Huleihel (COLT, 2018)

Optimal Single Sample Tests for Structured versus Unstructured Network Data. - Guy Bresler; Dheeraj Nagaraj (COLT, 2018)

Information Storage in the Stochastic Ising Model at Zero Temperature. - Ziv Goldfeld; Guy Bresler; Yury Polyanskiy (ISIT, 2018)

Sparse PCA from Sparse Linear Regression. - Guy Bresler; Sung Min Park 002; Madalina Persu (NeurIPS, 2018)

Learning Restricted Boltzmann Machines via Influence Maximization. - Guy Bresler; Frederic Koehler; Ankur Moitra; Elchanan Mossel (CoRR, 2018)

Learning Graphical Models From the Glauber Dynamics. - Guy Bresler; David Gamarnik; Devavrat Shah (IEEE Trans. Inf. Theory, 2018)

Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness. - Matthew S. Brennan; Guy Bresler (COLT, 2019)

Universality of Computational Lower Bounds for Submatrix Detection. - Matthew S. Brennan; Guy Bresler; Wasim Huleihel (COLT, 2019)

The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs. - Enric Boix-Adserà; Matthew S. Brennan; Guy Bresler (FOCS, 2019)

Information Storage in the Stochastic Ising Model at Low Temperature. - Ziv Goldfeld; Guy Bresler; Yury Polyanskiy (ISIT, 2019)

Sample Efficient Active Learning of Causal Trees. - Kristjan H. Greenewald; Dmitriy Katz; Karthikeyan Shanmugam; Sara Magliacane; Murat Kocaoglu; Enric Boix Adserà; Guy Bresler (NeurIPS, 2019)

Learning restricted Boltzmann machines via influence maximization. - Guy Bresler; Frederic Koehler; Ankur Moitra (STOC, 2019)

Average-Case Lower Bounds for Learning Sparse Mixtures, Robust Estimation and Semirandom Adversaries. - Matthew S. Brennan; Guy Bresler (CoRR, 2019)

Phase Transitions for Detecting Latent Geometry in Random Graphs. - Matthew S. Brennan; Guy Bresler; Dheeraj Nagaraj (CoRR, 2019)

Reducibility and Statistical-Computational Gaps from Secret Leakage. - Matthew S. Brennan; Guy Bresler (COLT, 2020)

A Corrective View of Neural Networks: Representation, Memorization and Learning. - Guy Bresler; Dheeraj Nagaraj (COLT, 2020)

Minimax Prediction in Tree Ising Models. - Guy Bresler; Mina Karzand (ISIT, 2020)

Learning Restricted Boltzmann Machines with Sparse Latent Variables. - Guy Bresler; Rares-Darius Buhai (NeurIPS, 2020)

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. - Guy Bresler; Dheeraj Nagaraj (NeurIPS, 2020)

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. - Dheeraj Nagaraj; Xian Wu 009; Guy Bresler; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2020)

Learning Restricted Boltzmann Machines with Few Latent Variables. - Guy Bresler; Rares-Darius Buhai (CoRR, 2020)

Editorial. - Devavrat Shah; Guy Bresler; John C. Duchi; Po-Ling Loh; Yihong Wu 001; Christina Lee Yu (IEEE J. Sel. Areas Inf. Theory, 2020)

Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. - Matthew S. Brennan; Guy Bresler; Samuel B. Hopkins 001; Jerry Li 001; Tselil Schramm (COLT, 2021)

Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models. - Enric Boix-Adserà; Guy Bresler; Frederic Koehler (FOCS, 2021)

The Algorithmic Phase Transition of Random k-SAT for Low Degree Polynomials. - Guy Bresler; Brice Huang (FOCS, 2021)

The staircase property: How hierarchical structure can guide deep learning. - Emmanuel Abbe; Enric Boix-Adserà; Matthew S. Brennan; Guy Bresler; Dheeraj Nagaraj (NeurIPS, 2021)

De Finetti-Style Results for Wishart Matrices: Combinatorial Structure and Phase Transitions. - Matthew S. Brennan; Guy Bresler; Brice Huang (CoRR, 2021)

Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering. - Guy Bresler; Mina Karzand (IEEE Trans. Inf. Theory, 2021)

Information Storage in the Stochastic Ising Model. - Ziv Goldfeld; Guy Bresler; Yury Polyanskiy (IEEE Trans. Inf. Theory, 2021)

Linear Programs with Polynomial Coefficients and Applications to 1D Cellular Automata. - Guy Bresler; Chenghao Guo; Yury Polyanskiy (CoRR, 2022)

The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures. - Nir Weinberger; Guy Bresler (J. Mach. Learn. Res., 2022)

Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique. - Guy Bresler; Tianze Jiang (COLT, 2023)

Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra Triangles. - Guy Bresler; Chenghao Guo; Yury Polyanskiy (FOCS, 2023)

Random Algebraic Graphs and Their Convergence to Erdos-Renyi. - Kiril Bangachev; Guy Bresler (CoRR, 2023)

Detection of L∞ Geometry in Random Geometric Graphs: Suboptimality of Triangles and Cluster Expansion. - Kiril Bangachev; Guy Bresler (COLT, 2024)

Thresholds for Reconstruction of Random Hypergraphs From Graph Projections. - Guy Bresler; Chenghao Guo; Yury Polyanskiy (COLT, 2024)

On the Fourier Coefficients of High-Dimensional Random Geometric Graphs. - Kiril Bangachev; Guy Bresler (STOC, 2024)

Efficient reductions between some statistical models. - Mengqi Lou; Guy Bresler; Ashwin Pananjady (CoRR, 2024)

Threshold for detecting high dimensional geometry in anisotropic random geometric graphs. - Matthew S. Brennan; Guy Bresler; Brice Huang (Random Struct. Algorithms, 2024)

Partial and Exact Recovery of a Random Hypergraph from its Graph Projection. - Guy Bresler; Chenghao Guo; Yury Polyanskiy; Andrew Yao (COLT, 2025)

Computational Equivalence of Spiked Covariance and Spiked Wigner Models via Gram-Schmidt Perturbation. - Guy Bresler; Alina Harbuzova (COLT, 2025)

Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and Enumeration. - Kiril Bangachev; Guy Bresler (STOC, 2025)

Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations. - Kiril Bangachev; Guy Bresler; Stefan Tiegel; Vinod Vaikuntanathan (STOC, 2025)

Optimal Sequential Recommendations: Exploiting User and Item Structure. - Mina Karzand; Guy Bresler (CoRR, 2025)

Computationally Efficient Reductions Between Some Statistical Models. - Mengqi Lou; Guy Bresler; Ashwin Pananjady (IEEE Trans. Inf. Theory, 2025)