Genre
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
We propose a versatile framework that combines DEQ with off-the-shelf machine learning models for predicting Hamiltonians.
Streaming PCA for Markovian Data
Since its inception in 1982, Oja's algorithm has become an established method for streaming principle component analysis (PCA).
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification Kaibo Wang
Diffusion-based purification has demonstrated impressive robustness as an adversarial defense.
Lo-Hi: Practical ML Drug Discovery Benchmark
Finding new drugs is getting harder and harder. One of the hopes of drug discovery is to use machine learning models to predict molecular properties.
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM
Single particle cryo-electron microscopy (cryo-EM) is a widely used imaging technique for visualizing biomolecular complexes at near-atomic resolution.
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox
We further show the mismatched sampling paradox: A learner who knows the rewards distributions and samples from the correct posterior distribution can perform exponentially worse than a learner who does not know the rewards and simply samples from a well-chosen Gaussian posterior.