I am a Ph.D student in computer science at the Courant Institute of
Mathematical Sciences, advised by Yann LeCun.
For the past three summers I interned at Facebook AI Research.
Before that I worked at the Center for
Health Informatics and Bioinformatics at the NYU Medical Center, and finished
my M.S. in math at NYU.
Earlier still, I did my undergrad in pure math at the University of Texas at Austin.
My current research interests are in deep learning, reasoning and memory.
Tracking the World State with Recurrent Entity Networks
Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes and Yann LeCun (ICLR 2017)
[Press (Le Monde)]
Recurrent Orthogonal Networks and Long-Memory Tasks
Mikael Henaff, Arthur Szlam and Yann LeCun (ICML 2016)
Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery
Alexander Statnikov, Sisi Ma, Mikael Henaff, Nikita Lytkin, Efstratios Efstathiadis, Eric R Peskin, Constantin F Aliferis (JMLR 2016)
The Loss Surface of Multilayer Networks
Anna Choromanska, Mikael Henaff, Michael Mathieu, Gerard Ben Arous, Yann LeCun (AISTATS 2015)
Fast Training of Convolutional Networks through FFTs
Michael Mathieu, Mikael Henaff and Yann LeCun (ICLR 2014)
Information Content and Analysis Methods for Multi-Modal High-Throughput Biomedical Data.
Bisakha Ray, Mikael Henaff, Sisi Ma, Efstratios Efstathiadis,
Eric Peskin, Marco Picone, Tito Poli, Constantin Aliferis and Alexander
Statnikov (Nature Scientific Reports, 2014)
Microbiomic Signatures of Psoriasis: Feasibility and Methodology Comparison.
Alexander Statnikov, Alexander Alekseyenko, Zhiguo Li, Mikael Henaff,
Martin Blaser and Constantin Aliferis
(Nature Scientific Reports, 2013)
A Comprehensive Evaluation of Multicategory Classification Methods for
Alexander Statnikov, Mikael Henaff, Varun Narendra,
Kranti Konganti, Zhiguo Li, Liying Yang, Zhiheng Pei, Martin Blaser,
Constantin Aliferis and Alexander Alekseyenko.
New Methods for Separating Causes from Effects in Genomic Data
Alexander Statnikov, Mikael Henaff, Nikita Lytkin and Constantin Aliferis.
(BMC Genomics, 2012)
Unsupervised Learning of Sparse Features for Scalable Audio Classification
Mikael Henaff, Kevin Jarrett, Koray Kavukcuoglu and Yann LeCun (ISMIR 2011)
Contact: mbh305 [at] nyu [dot] edu
Deep Convolutional Networks on Graph-Structured Data
Mikael Henaff, Joan Bruna and Yann LeCun (arXiv 2015)