An Information-Percolation Bound for Spin Synchronization on General Graphs. - Emmanuel Abbe; Enric Boix (CoRR, 2018)

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

Subadditivity Beyond Trees and the Chi-Squared Mutual Information. - Emmanuel Abbe; Enric Boix Adserà (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)

Randomized Concurrent Set Union and Generalized Wake-Up. - Siddhartha V. Jayanti; Robert E. Tarjan; Enric Boix-Adserà (PODC, 2019)

Approximating the Determinant of Well-Conditioned Matrices by Shallow Circuits. - Enric Boix-Adserà; Lior Eldar; Saeed Mehraban (CoRR, 2019)

High-precision Wasserstein barycenters in polynomial time. - Jason M. Altschuler; Enric Boix-Adserà (CoRR, 2020)

Graph Powering and Spectral Robustness. - Emmanuel Abbe; Enric Boix-Adserà; Peter Ralli; Colin Sandon (SIAM J. Math. Data Sci., 2020)

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

Hardness results for Multimarginal Optimal Transport problems. - Jason M. Altschuler; Enric Boix-Adserà (Discret. Optim., 2021)

The multiplayer Colonel Blotto game. - Enric Boix-Adserà; Benjamin L. Edelman; Siddhartha Jayanti (Games Econ. Behav., 2021)

Wasserstein barycenters can be computed in polynomial time in fixed dimension. - Jason M. Altschuler; Enric Boix-Adserà (J. Mach. Learn. Res., 2021)

The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks. - Emmanuel Abbe; Enric Boix Adserà; Theodor Misiakiewicz (COLT, 2022)

On the non-universality of deep learning: quantifying the cost of symmetry. - Emmanuel Abbe; Enric Boix-Adserà (NeurIPS, 2022)

GULP: a prediction-based metric between representations. - Enric Boix-Adserà; Hannah Lawrence; George Stepaniants; Philippe Rigollet (NeurIPS, 2022)

Wasserstein Barycenters Are NP-Hard to Compute. - Jason M. Altschuler; Enric Boix-Adserà (SIAM J. Math. Data Sci., 2022)

SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics. - Emmanuel Abbe; Enric Boix Adserà; Theodor Misiakiewicz (COLT, 2023)

Transformers learn through gradual rank increase. - Emmanuel Abbe; Samy Bengio; Enric Boix-Adserà; Etai Littwin; Joshua M. Susskind (NeurIPS, 2023)

The NTK approximation is valid for longer than you think. - Enric Boix-Adserà; Etai Littwin (CoRR, 2023)

PROPANE: Prompt design as an inverse problem. - Rimon Melamed; Lucas H. McCabe; Tanay Wakhare; Yejin Kim; H. Howie Huang; Enric Boix-Adserà (CoRR, 2023)

Tight conditions for when the NTK approximation is valid. - Enric Boix-Adserà; Etai Littwin (Trans. Mach. Learn. Res., 2023)

Polynomial-time algorithms for multimarginal optimal transport problems with structure. - Jason M. Altschuler; Enric Boix-Adserà (Math. Program., 2023)

Prompts have evil twins. - Rimon Melamed; Lucas H. McCabe; Tanay Wakhare; Yejin Kim; H. Howie Huang; Enric Boix-Adserà (EMNLP, 2024)

When can transformers reason with abstract symbols? - Enric Boix-Adserà; Omid Saremi; Emmanuel Abbe; Samy Bengio; Etai Littwin; Joshua M. Susskind (ICLR, 2024)

Towards a theory of model distillation. - Enric Boix-Adserà (CoRR, 2024)

Characterizations of how neural networks learn - Enric Boix-Adserà (2024)

On the inductive bias of infinite-depth ResNets and the bottleneck rank. - Enric Boix-Adserà (CoRR, 2025)

Aggregate and conquer: detecting and steering LLM concepts by combining nonlinear predictors over multiple layers. - Daniel Beaglehole; Adityanarayanan Radhakrishnan; Enric Boix-Adserà; Mikhail Belkin (CoRR, 2025)

The power of fine-grained experts: Granularity boosts expressivity in Mixture of Experts. - Enric Boix-Adserà; Philippe Rigollet (CoRR, 2025)

Let Me Think! A Long Chain-of-Thought Can Be Worth Exponentially Many Short Ones. - Parsa Mirtaheri; Ezra Edelman; Samy Jelassi; Eran Malach; Enric Boix-Adserà (CoRR, 2025)

FACT: the Features At Convergence Theorem for neural networks. - Enric Boix-Adserà; Neil Mallinar; James B. Simon; Mikhail Belkin (CoRR, 2025)