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Found 7 papers, 4 papers with code
DockGame: Cooperative Games for Multimeric Rigid Protein Docking
Most traditional and deep learning methods for docking have focused mainly on binary docking, following either a search-based, regression-based, or generative modeling paradigm.
Adaptive Conformal Regression with Jackknife+ Rescaled Scores
We address this with a new adaptive method based on rescaling conformal scores with an estimate of local score distribution, inspired by the Jackknife+ method, which enables the use of calibration data in conformal scores without breaking calibration-test exchangeability.
Aligned Diffusion Schrödinger Bridges
Diffusion Schr\"odinger bridges (DSB) have recently emerged as a powerful framework for recovering stochastic dynamics via their marginal observations at different time points.
Practical and scalable simulations of non-Markovian stochastic processes
While analytic solutions often cannot be derived, existing simulation frameworks can generate stochastic trajectories compatible with the dynamical laws underlying the random phenomena.
It's FLAN time! Summing feature-wise latent representations for interpretability
Interpretability has become a necessary feature for machine learning models deployed in critical scenarios, e. g. legal system, healthcare.
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks
Less than 1% of protein sequences are structurally and functionally annotated.
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer
We present the Network-based Biased Tree Ensembles (NetBiTE) method for drug sensitivity prediction and drug sensitivity biomarker identification in cancer using a combination of prior knowledge and gene expression data.
