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04/07/2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks
Geometric deep learning enables the encoding of physical symmetries in m...
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02/03/2023
Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction
Modern machine learning techniques have been extensively applied to mate...
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10/24/2022
Structure-based Drug Design with Equivariant Diffusion Models
Structure-based drug design (SBDD) aims to design small-molecule ligands...
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06/28/2022
Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning
Despite the success of practical solvers in various NP-complete domains ...
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06/16/2022
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation
Bayesian Optimization (BO) has shown great promise for the global optimi...
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12/02/2021
Constrained Machine Learning: The Bagel Framework
Machine learning models are widely used for real-world applications, suc...
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10/22/2021
Contrastively Disentangled Sequential Variational Autoencoder
Self-supervised disentangled representation learning is a critical task ...
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06/11/2021
Sparse Bayesian Learning via Stepwise Regression
Sparse Bayesian Learning (SBL) is a powerful framework for attaining spa...
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06/06/2021
On the Optimality of Backward Regression: Sparse Recovery and Subset Selection
Sparse recovery and subset selection are fundamental problems in varied ...
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03/09/2021
HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders
Understanding how environmental characteristics affect bio-diversity pat...
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02/16/2021
Evaluating Multi-label Classifiers with Noisy Labels
Multi-label classification (MLC) is a generalization of standard classif...
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12/27/2020
Understanding Decoupled and Early Weight Decay
Weight decay (WD) is a traditional regularization technique in deep lear...
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09/07/2020
Efficient Projection Algorithms onto the Weighted l1 Ball
Projected gradient descent has been proved efficient in many optimizatio...
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07/12/2020
Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model
Multi-label classification is the challenging task of predicting the pre...
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06/10/2019
Tackling Climate Change with Machine Learning
Climate change is one of the greatest challenges facing humanity, and we...
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02/14/2019
Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy
We propose a novel exponentially-modified Gaussian (EMG) mixture residua...
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06/01/2018
Understanding Batch Normalization
Batch normalization is a ubiquitous deep learning technique that normali...
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05/07/2018
Imitation Refinement
Many real-world tasks involve identifying patterns from data satisfying ...
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11/18/2017
Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network
Cascades represent rapid changes in networks. A cascading phenomenon of ...
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09/28/2016
Deep Multi-Species Embedding
Understanding how species are distributed across landscapes over time is...
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11/27/2014