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01/14/2023
Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning
Drug combination therapy is a well-established strategy for disease trea...
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11/30/2022
xTrimoABFold: Improving Antibody Structure Prediction without Multiple Sequence Alignments
In the field of antibody engineering, an essential task is to design a n...
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10/26/2022
ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select
We study the problem of extracting N-ary relation tuples from scientific...
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10/06/2022
Uncovering the Structural Fairness in Graph Contrastive Learning
Recent studies show that graph convolutional network (GCN) often perform...
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08/07/2022
SciAnnotate: A Tool for Integrating Weak Labeling Sources for Sequence Labeling
Weak labeling is a popular weak supervision strategy for Named Entity Re...
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07/28/2022
HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative
AI-based protein structure prediction pipelines, such as AlphaFold2, hav...
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06/28/2022
Graph Condensation via Receptive Field Distribution Matching
Graph neural networks (GNNs) enable the analysis of graphs using deep le...
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05/27/2022
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition
Weakly supervised named entity recognition methods train label models to...
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03/18/2022
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning
Weakly-supervised learning (WSL) has shown promising results in addressi...
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02/11/2022
Learning Temporal Rules from Noisy Timeseries Data
Events across a timeline are a common data representation, seen in diffe...
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12/14/2021
Efficient Dynamic Graph Representation Learning at Scale
Dynamic graphs with ordered sequences of events between nodes are preval...
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11/22/2021
A General Framework for Lifelong Localization and Mapping in Changing Environment
The environment of most real-world scenarios such as malls and supermark...
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11/03/2021
Multi-task Learning of Order-Consistent Causal Graphs
We consider the problem of discovering K related Gaussian directed acycl...
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10/27/2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization
We consider the problem of searching an input maximizing a black-box obj...
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10/26/2021
Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling
The Continuous-Time Hidden Markov Model (CT-HMM) is an attractive approa...
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10/07/2021
GNN is a Counter? Revisiting GNN for Question Answering
Question Answering (QA) has been a long-standing research topic in AI an...
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10/02/2021
ProTo: Program-Guided Transformer for Program-Guided Tasks
Programs, consisting of semantic and structural information, play an imp...
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05/26/2021
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
We study the problem of learning a named entity recognition (NER) tagger...
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05/17/2021
TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning
Dynamic graph modeling has recently attracted much attention due to its ...
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04/25/2021
Speeding up Computational Morphogenesis with Online Neural Synthetic Gradients
A wide range of modern science and engineering applications are formulat...
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03/22/2021
How to Design Sample and Computationally Efficient VQA Models
In multi-modal reasoning tasks, such as visual question answering (VQA),...
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03/18/2021
Concentric Spherical GNN for 3D Representation Learning
Learning 3D representations that generalize well to arbitrarily oriented...
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03/01/2021
A Biased Graph Neural Network Sampler with Near-Optimal Regret
Graph neural networks (GNN) have recently emerged as a vehicle for apply...
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11/04/2020
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders
The design/discovery of new materials is highly non-trivial owing to the...
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09/16/2020
DDRQA: Dynamic Document Reranking for Open-domain Multi-hop Question Answering
Open-domain multi-hop question answering (QA) requires to retrieve multi...
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09/16/2020
Question Directed Graph Attention Network for Numerical Reasoning over Text
Numerical reasoning over texts, such as addition, subtraction, sorting a...
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06/29/2020
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
Retrosynthetic planning is a critical task in organic chemistry which id...
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06/24/2020
Understanding Deep Architectures with Reasoning Layer
Recently, there has been a surge of interest in combining deep learning ...
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06/10/2020
Bandit Samplers for Training Graph Neural Networks
Several sampling algorithms with variance reduction have been proposed f...
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06/09/2020
Learning to Stop While Learning to Predict
There is a recent surge of interest in designing deep architectures base...
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04/19/2020
Intention Propagation for Multi-agent Reinforcement Learning
A hallmark of an AI agent is to mimic human beings to understand and int...
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04/09/2020
Orthogonal Over-Parameterized Training
The inductive bias of a neural network is largely determined by the arch...
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02/28/2020
DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding
Recent studies on open-domain question answering have achieved prominent...
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02/27/2020
Heterogeneous Graph Neural Networks for Malicious Account Detection
We present, GEM, the first heterogeneous graph neural network approach f...
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02/13/2020
RNA Secondary Structure Prediction By Learning Unrolled Algorithms
In this paper, we propose an end-to-end deep learning model, called E2Ef...
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01/29/2020
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Markov Logic Networks (MLNs), which elegantly combine logic rules and pr...
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01/06/2020
Retrosynthesis Prediction with Conditional Graph Logic Network
Retrosynthesis is one of the fundamental problems in organic chemistry. ...
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11/13/2019
Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM
Service robots should be able to operate autonomously in dynamic and dai...
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10/28/2019
Neural Similarity Learning
Inner product-based convolution has been the founding stone of convoluti...
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10/06/2019
Learn to Explain Efficiently via Neural Logic Inductive Learning
The capability of making interpretable and self-explanatory decisions is...
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06/23/2019
Optimal Solution Predictions for Mixed Integer Programs
Mixed Integer Programming (MIP) is one of the most widely used modeling ...
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06/12/2019
Compressive Hyperspherical Energy Minimization
Recent work on minimum hyperspherical energy (MHE) has demonstrated its ...
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06/05/2019
Can Graph Neural Networks Help Logic Reasoning?
Effectively combining logic reasoning and probabilistic inference has be...
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06/01/2019
GLAD: Learning Sparse Graph Recovery
Recovering sparse conditional independence graphs from data is a fundame...
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04/27/2019
Exponential Family Estimation via Adversarial Dynamics Embedding
We present an efficient algorithm for maximum likelihood estimation (MLE...
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02/28/2019
Learning to Plan via Neural Exploration-Exploitation Trees
Sampling-based algorithms such as RRT and its variants are powerful tool...
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02/07/2019
Cost-Effective Incentive Allocation via Structured Counterfactual Inference
We address a practical problem ubiquitous in modern industry, in which a...
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02/02/2019
Meta Particle Flow for Sequential Bayesian Inference
We present a particle flow realization of Bayes' rule, where an ODE-base...
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01/27/2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
We consider the networked multi-agent reinforcement learning (MARL) prob...
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12/27/2018