Search Results for author:
Found 14 papers, 4 papers with code
Predicting deliberative outcomes
Our games take as input, e. g., UN resolution to be voted on, and map such contexts to initial strategies, player utilities, and interactions.
Predicting deliberative outcomes
Our games take as input, e. g., UN resolution to be voted on, and map such contexts to initial strategies, player utilities, and interactions.
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
Climate and weather prediction traditionally relies on complex numerical simulations of atmospheric physics.
Field-based Molecule Generation
This work introduces FMG, a field-based model for drug-like molecule generation.
Algebraic Positional Encodings
We introduce a novel positional encoding strategy for Transformer-style models, addressing the shortcomings of existing, often ad hoc, approaches.
AbODE: Ab Initio Antibody Design using Conjoined ODEs
Antibodies are Y-shaped proteins that neutralize pathogens and constitute the core of our adaptive immune system.
Modular Flows: Differential Molecular Generation
Generating new molecules is fundamental to advancing critical applications such as drug discovery and material synthesis.
Provably expressive temporal graph networks
Specifically, novel constructions reveal the inadequacy of MP-TGNs and WA-TGNs, proving that neither category subsumes the other.
Why GANs are overkill for NLP
We show that, while it may seem that maximizing likelihood is inherently different than minimizing distinguishability, this distinction is largely artificial and only holds for limited models.
Generative Models for Graph-Based Protein Design
Engineered proteins offer the potential to solve many problems in biomedicine, energy, and materials science, but creating designs that succeed is difficult in practice.
Supervising Unsupervised Learning
We introduce a framework to transfer knowledge acquired from a repository of (heterogeneous) supervised datasets to new unsupervised datasets.
Local Aggregative Games
Aggregative games provide a rich abstraction to model strategic multi-agent interactions.
Learning Tree Structured Potential Games
Many real phenomena, including behaviors, involve strategic interactions that can be learned from data.
Adaptivity to Local Smoothness and Dimension in Kernel Regression
We present the first result for kernel regression where the procedure adapts locally at a point $x$ to both the unknown local dimension of the metric and the unknown H\{o}lder-continuity of the regression function at $x$.
