Tensor Reed-Muller Codes: Achieving Capacity with Quasilinear Decoding Time

E. Abbe; C. Sandon; O. Sprumont 

Future cardiovascular events prediction from invasive coronary angiography: A graph representation learning perspective

X. Sun; T. Belmpas; O. Senouf; E. Abbé; P. Frossard et al. 

k-server-bench: Automating Potential Discovery for the $k$-Server Conjecture

K. Brilliantov; E. Bamas; E. Abbé 

ODySSeI: An Open-Source End-to-End Framework for Automated Detection, Segmentation, and Severity Estimation of Lesions in Invasive Coronary Angiography Images

A. Choudhary; X. Sun; T. Mahendiran; O. Y. Senouf; D. Auberson et al. 

Comment l’intelligence artificielle peut-elle améliorer la prévention cardiovasculaire ?

A. A. Mircea; E. Abbé; A. Mackowiak; B. Gencer; D. Locca et al. 

AbstRaL: Augmenting LLMs’ Reasoning by Reinforcing Abstract Thinking

S. Gao; A. Bosselut; S. Bengio; E. Abbé 

Inductive Domain Transfer In Misspecified Simulation-Based Inference

O. Y. Senouf; A. Wehenkel; C. Vincent-Cuaz; E. Abbé; P. Frossard 

Physics-informed self-supervised learning for predictive modeling of coronary artery digital twins

X. Sun; T. Mahendiran; O. Y. Senouf; D. Auberson; B. De Bruyne et al. 

AI-Driven multi-view learning from CCTA for myocardial infarction diagnosis

J. Gwizdała; A. Salihu; O. Senouf; D. Meier; D. C. Rotzinger et al. 

CM-UNet: A Self-Supervised Learning-Based Model for Coronary Artery Segmentation in X-Ray Angiography

C. Challier; X. Sun; T. Mahendiran; O. Y. Senouf; B. De Bruyne et al. 

Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning

A. Surina; C. Gulcehre; E. Abbé; M. Viazovska; A. Seddas et al. 

Reed-Muller Codes for Quantum Pauli and Multiple Access Channels

D. Abdelhadi; C. Sandon; E. Abbe; R. Urbanke 

What Makes the Preferred Thinking Direction for LLMs in Multiple-choice Questions?

Y. Zhang; R. Bai; Z. GU; R. Zhang; J. Gu et al. 

Boosted decoders for reed-muller codes

E. Abbe; C. Sandon 

Learning to Reason with Neural Networks: Principles and Methods

Learning High-Degree Parities: The Crucial Role of the Initialization

E. Abbe; E. Cornacchia; J. Hązła; D. Kougang-Yombi 

Informed machine learning models for advancing cardiac disease prognosis

Learning High-Degree Parities: The Crucial Role of the Initialization

E. Abbé; E. Cornacchia; J. Hązła; D. Kougang-Yombi 

Polynomial Freiman-Ruzsa, Reed-Muller codes and Shannon capacity

E. Abbé; C. P. Sandon; V. Shashkov; M. Viazovska 

Generalization on the Unseen, Logic Reasoning and Degree Curriculum

E. Abbe; S. Bengio; A. Lotfi; K. Rizk 

angioPy: an open-source, deep learning-driven tool for coronary artery segmentation

T. Mahendiran; D. Thanou; O. Y. Senouf; Y. Jamaa; S. Fournier et al. 

Assessing the need for coronary angiography in high-risk acute coronary syndrome patients using artificial intelligence and computed tomography

A. Salihu; A. Cagnina; D. Meier; I. Skalidis; W. Luangphiphat et al. 

Chain-of-Sketch: Enabling Global Visual Reasoning

A. Lotfi; E. Fini; S. Bengio; M. Nabi; E. Abbé 

AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation

T. Mahendiran; D. Thanou; O. Y. Senouf; Y. Jamaa; S. Fournier et al. 

Future cardiovascular events prediction from invasive coronary angiography: A graph representation learning perspective

X. Sun; T. Belmpas; O. Y. Senouf; E. Abbé; P. Frossard et al. 

A study of ChatGPT in facilitating Heart Team decisions on severe aortic stenosis

A. Salihu; D. Meier; N. Noirclerc; I. Skalidis; S. Mauler-Wittwer et al. 

When can transformers reason with abstract symbols?

E. Boix-Adserà; O. Saremi; E. Abbe; S. Bengio; E. Littwin et al. 

Generalization on the Unseen, Logic Reasoning and Degree Curriculum

E. Abbe; S. Bengio; A. Lotfi; K. Rizk 

Transformation-invariant Learning and Theoretical Guarantees for Ood Generalization

O. Montasser; H. Shao; E. Abbe 

Gender Bias in AI’s Perception of Cardiovascular Risk

M. Achtari; A. Salihu; O. Muller; E. Abbé; C. Clair et al. 

How Far Can Transformers Reason? the Globality Barrier and Inductive Scratchpad

E. Abbe; S. Bengio; A. Lotfi; C. Sandon; O. Saremi 

Graph Neural Network based Future Clinical Events Prediction from Invasive Coronary Angiography

X. Sun; T. Belmpas; O. Y. Senouf; E. Abbe; P. Frossard et al. 

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction

I. D. Sievering; O. Senouf; T. Mahendiran; D. Nanchen; S. Fournier et al. 

On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions

D. Pushkin; R. Berthier; E. Abbe 

Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography

A. Cagnina; A. Salihu; D. Meier; W. Luangphiphat; B. Faltin et al. 

Reed-Muller codes have vanishing bit-error probability below capacity: a simple tighter proof via camellia boosting

E. Abbé; C. Sandon 

Towards AI-assisted cardiology: a reflection on the performance and limitations of using large language models in clinical decision-making

A. Salihu; M. A. Gadiri; I. Skalidis; D. Meier; D. Auberson et al. 

Gender Bias in AI’s Perception of Cardiovascular Risk (Preprint)

M. Achtari; A. Salihu; O. Müller; E. Abbé; C. Clair et al. 

ChatGPT takes on the european exam in core cardiology: an AI success story

I. Skalidis; A. Cagnina; O. Luangphiphat; O. Muller; E. Abbe et al. 

When can transformers reason with abstract symbols?

E. Boix-Adserà; O. Saremi; E. Abbé; S. Bengio; E. Littwin et al. 

Boolformer: Symbolic Regression of Logic Functions with Transformers

S. d’Ascoli; A. Renard; V. Papadopoulos; S. Bengio; J. Susskind et al. 

Polynomial-time universality and limitations of deep learning

E. Abbe; C. Sandon 

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

I. Skalidis; A. Cagnina; W. Luangphiphat; T. Mahendiran; O. Muller et al. 

Les dispositifs intelligents et l’IA en cardiologie peuvent-ils améliorer la pratique clinique ?

N. Maurizi; I. Skalidis; D. Auberson; T. Mahendiran; S. Fournier et al. 

Learning Sparse Graphons And The Generalized Kesten-Stigum Threshold

E. Abbe; S. Li; A. Sly 

Transformers learn through gradual rank increase

E. Boix-Adserà; E. Littwin; E. Abbe; S. Bengio; J. Susskind 

A proof that Reed-Muller codes achieve Shannon capacity on symmetric channels

E. Abbe; C. P. Sandon 

Reed-Muller Codes

E. Abbé; O. Sberlo; A. Shpilka; M. Ye 

Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs

E. Abbe; E. Cornacchia; A. Lotfi 

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Deep learning-based prediction of future myocardial infarction using invasive coronary angiography: a feasibility study

T. Mahendiran; D. Thanou; O. Senouf; D. Meier; N. Dayer et al. 

Can Knowledge Transfer Techniques Compensate for the Limited Myocardial Infarction Data by Leveraging Haemodynamics? An in silico Study

R. Tenderini; F. Betti; O. Y. Senouf; O. Muller; S. Deparis et al. 

SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics

E. Abbe; E. Boix-Adserà; T. Misiakiewicz 

Anatomy-informed multimodal learning for myocardial infarction prediction

I-D. Sievering; O. Y. Senouf; T. Mahendiran; D. Nanchen; S. Fournier et al. 

Attention-based learning of views fusion applied to myocardial infarction diagnosis from x-ray CT

J. J. Gwizdala; O. Y. Senouf; D. Auberson; D. Meier; D. Rotzinger et al. 

An 𝓁 p theory of PCA and spectral clustering

E. Abbe; J. Fan; K. Wang 

L’intelligence artificielle et la cardiologie : la machine est lancée

O. Muller; E. Abbé; F. Mach 

An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn

E. Abbe; E. Cornacchia; J. Hazla; C. Marquis 

Binary Perceptron: Efficient Algorithms Can Find Solutions in a RareWell-Connected Cluster

E. Abbe; S. Li; A. Sly 

The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks

E. Abbe; E. Boix-Adserà; T. Misiakiewicz 

Proof of the Contiguity Conjecture and Lognormal Limit for the Symmetric Perceptron

E. Abbé; S. Li; A. Sly 

Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures

E. Abbe; S. Bengio; E. Cornacchia; J. Kleinberg; A. Lotfi et al. 

On the non-universality of deep learning: quantifying the cost of symmetry

E. Abbe; E. Boix-Adserà 

Almost-Reed-Muller Codes Achieve Constant Rates for Random Errors

E. Abbe; J. Hazla; I. Nachum 

Binary perceptron: efficient algorithms can find solutions in a rare well-connected cluster

E. Abbé; S. Li; A. Sly 

Reed-Muller Codes: Theory and Algorithms

E. Abbe; A. Shpilka; M. Ye 

Predicting future myocardial infarction from angiographies with deep learning

D. Thanou; O. Y. Senouf; O. Raita; E. Abbé; P. Frossard et al. 

Stochastic block model entropy and broadcasting on trees with survey

E. Abbe; E. Cornacchia; Y. Gu; Y. Polyanskiy 

The staircase property: How hierarchical structure can guide deep learning

E. Abbe; E. Boix-Adsera; M. Brennan; G. Bresler; D. Nagaraj 

On the Power of Differentiable Learning versus PAC and SQ Learning

E. Abbe; P. Kamath; E. Malach; C. Sandon; N. Srebro 

Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels

E. Malach; P. Kamath; E. Abbe; N. Srebro 

Reed-Muller Codes Polarize

E. Abbe; M. Ye 

Recursive Projection-Aggregation Decoding of Reed-Muller Codes

M. Ye; E. Abbe 

Maximum Multiscale Entropy and Neural Network Regularization

A. R. Asadi; E. Abbé 

An $\ell_p$ theory of PCA and spectral clustering

E. Abbé; J. Fan; K. Wang 

An Alon-Boppana theorem for powered graphs and generalized Ramanujan graphs

E. Abbé; P. Ralli 

Learning Sparse Graphons and the Generalized Kesten-Stigum Threshold

E. Abbé; S. Li; A. Sly 

Entrywise eigenvector analysis of random matrices with low expected rank

E. Abbe; J. Fan; K. Wang; Y. Zhong 

An information-percolation bound for spin synchronization on general graphs

E. Abbé; E. Boix-Adserà 

Community Detection on Euclidean Random Graphs

E. Abbé; F. Baccelli; A. Sankararaman 

From Information Inequalities to Computational Lower Bounds in Learning

E. Abbé 

Generalized nonbacktracking bounds on the influence in independent cascade models

E. Abbe; S. Kulkarni; E. J. Lee 

Poly-time universality and limitations of deep learning

E. Abbé; C. Sandon 

System and method for decoding reed-muller codes

M. Ye; E. Abbe 

Polarization in Attraction-Repulsion Models

E. Comacchia; N. Singer; E. Abbe 

On the universality of deep learning

E. Abbe; C. Sandon 

Graph Powering and Spectral Robustness

E. Abbe; E. Boix-Adsera; P. Ralli; C. Sandon 

Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks

A. R. Asadi; E. Abbe 

Entropic Matroids and Their Representation

E. Abbe; S. Spirkl 

Recursive projection-aggregation decoding of Reed-Muller codes

M. Ye; E. Abbe 

Chaining Meets Chain Rule: Multilevel Entropic Regularization and\n Training of Neural Nets

A. R. Asadi; E. Abbé 

Subadditivity Beyond Trees and the Chi-Squared Mutual Information

E. Abbe; E. B. Adsera 

Reed-Muller codes polarize

E. Abbe; M. Ye 

Multireference Alignment Is Easier With an Aperiodic Translation Distribution

E. Abbé; T. Bendory; W. Leeb; J. M. Pereira; N. Sharon et al. 

Provable limitations of deep learning

E. Abbé; C. Sandon 

Estimation in the Group Action Channel

E. Abbe; J. M. Pereira; A. Singer 

Community Detection and Stochastic Block Models

E. Abbe 

Learning from graphical data

E. Abbé 

Chaining Mutual Information and Tightening Generalization Bounds

A. R. Asadi; E. Abbe; S. Verdu 

Group synchronization on grids

E. Abbe; L. Massoulié; A. Montanari; A. Sly; N. Srivastava 

Communication-computation efficient gradient coding

M. Ye; E. Abbe 

Community Detection and Stochastic Block Models

E. Abbé 

Nonbacktracking bounds on the influence in independent cascade models

E. Abbe; S. Kulkarni; E. J. Lee 

Polarization of the Renyi Information Dimension With Applications to Compressed Sensing

S. Haghighatshoar; E. Abbé 

Asymptotic mutual information for the balanced binary stochastic block model

Y. Deshpande; E. Abbe; A. Montanari 

Polar Codes for Broadcast Channels

N. Goela; E. Abbé; M. C. Gastpar 

A New Entropy Power Inequality for Integer-Valued Random Variables

S. Haghighatshoar; E. Abbe; I. E. Telatar 

Proof of the Outage Probability Conjecture for MISO Channels

E. Abbe; S-L. Huang; E. Telatar 

Polar Codes For Broadcast Channels

N. Goela; E. Abbé; M. C. Gastpar 

Polar Codes for the m-User Multiple Access Channel

E. Abbe; E. Telatar 

Adaptive sensing using deterministic partial Hadamard matrices

S. Haghighatshoar; E. Abbé; E. Telatar 

Polar Codes for the m-User MAC

E. Abbe; E. Telatar 

A coordinate system for Gaussian Networks

E. Abbe; Z. Lizhong 

On the concentration of the number of solutions of random satisfiability formulas

E. Abbe; A. Montanari 

Polarization and randomness extraction

E. Abbe 

Polar coding schemes for the AWGN channel

E. Abbe; A. Barron 

Universal Source Polarization and Spare Recovery

E. Abbe 

Polar codes for the m-user multiple access channel and matroids

E. Abbe; E. Telatar 

Universal a posteriori metrics game

E. Abbe; R. Pulikkoonattu 

Coding along Hermite polynomials for interference channels

E. Abbe; L. Zheng 

Coding Along Hermite Polynomials for Gaussian Noise Channels

E. Abbé; L. Zheng 

Normalization and correlation of cross-nested logit models

E. Abbé; M. Bierlaire; T. Toledo 

Normalization and correlation of cross-nested logit models

E. Abbé; M. Bierlaire; T. Toledo 

Normalization and correlation of cross-nested logit models

M. Bierlaire; E. Abbé; T. Toledo