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06/08/2023
Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction
Protein-ligand binding affinity (PLBA) prediction is the fundamental tas...
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01/12/2023
Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening
Recently, machine learning methods have been used to propose molecules w...
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01/03/2023
Protein-Ligand Complex Generator Drug Screening via Tiered Tensor Transform
Accurate determination of a small molecule candidate (ligand) binding po...
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09/23/2022
Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation
Session-based recommendation (SBR) systems aim to utilize the user's sho...
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08/16/2022
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries
Knowledge graph (KG) embeddings have been a mainstream approach for reas...
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12/02/2021
Learning Large-scale Network Embedding from Representative Subgraph
We study the problem of large-scale network embedding, which aims to lea...
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10/25/2021
NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization
In this work, we propose NetMF+, a fast, memory-efficient, scalable, and...
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10/08/2021
Stable Prediction on Graphs with Agnostic Distribution Shift
Graph is a flexible and effective tool to represent complex structures i...
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09/15/2021
Fast Extraction of Word Embedding from Q-contexts
The notion of word embedding plays a fundamental role in natural languag...
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08/17/2021
Modeling Protein Using Large-scale Pretrain Language Model
Protein is linked to almost every life process. Therefore, analyzing the...
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03/24/2021
FastMoE: A Fast Mixture-of-Expert Training System
Mixture-of-Expert (MoE) presents a strong potential in enlarging the siz...
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03/18/2021
All NLP Tasks Are Generation Tasks: A General Pretraining Framework
There have been various types of pretraining architectures including aut...
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08/06/2020
Concentration Bounds for Co-occurrence Matrices of Markov Chains
Co-occurrence statistics for sequential data are common and important da...
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06/17/2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
Graph representation learning has emerged as a powerful technique for re...
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11/07/2019
Blockwise Self-Attention for Long Document Understanding
We present BlockBERT, a lightweight and efficient BERT model that is des...
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06/26/2019
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
We study the problem of large-scale network embedding, which aims to lea...
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06/22/2019
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models
We introduce a new molecular dataset, named Alchemy, for developing mach...
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07/15/2018
DeepInf: Social Influence Prediction with Deep Learning
Social and information networking activities such as on Facebook, Twitte...
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10/09/2017