Maximilian Nickel

RESEARCH SCIENTIST | NEW YORK CITY, UNITED STATES

Maximilian Nickel is a Research Scientist at Facebook AI Research in New York. Before joining FAIR, he was a postdoctoral fellow at MIT where he was with the Laboratory for Computational and Statistical Learning and the Center for Brains, Minds and Machines. In 2013, he received his PhD with summa cum laude from the Ludwig Maximilian University Munich. From 2010 to 2013 he worked as a research assistant at Siemens Corporate Technology. His research centers around geometric methods for learning and reasoning with relational knowledge representations and their applications in artificial intelligence and network science.

Maximilian's Publications

June 21, 2022

Matching Normalizing Flows and Probability Paths on Manifolds

Yaron Lipman, Brandon Amos, Max Nickel, Ricky Chen, Samuel Cohen, Aditya Grover, Heli Ben-Hamu, Joey Bose

June 21, 2022

November 05, 2021

CORE MACHINE LEARNING

Moser Flow: Divergence-based Generative Modeling on Manifolds

Noam Rozen, Aditya Grover, Max Nickel, Yaron Lipman

November 05, 2021

December 11, 2020

CORE MACHINE LEARNING

Deep Riemannian Manifold Learning

Brandon Amos, Max Nickel, Aaron Lou

December 11, 2020

November 20, 2020

RESEARCH

Riemannian Continuous Normalizing Flows

Maximilian Nickel, Emile Mathieu

November 20, 2020

September 23, 2020

ML APPLICATIONS

Neural Relational Autoregression for High-Resolution COVID-19 Forecasting

Maximilian Nickel, Levent Sagun, Mark Ibrahim, Matt Le, Timothee Lacroix

September 23, 2020

October 25, 2019

RESEARCH

NLP

Revisiting the Evaluation of Theory of Mind through Question Answering

Max Nickel, Matt Le, Y-Lan Boureau

October 25, 2019

July 16, 2018

RESEARCH

SPEECH & AUDIO

Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora

Max Nickel, Douwe Kiela, Stephen Roller

July 16, 2018