Spain

ECAI 2020

DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction

drug-target binding affinity prediction

representation learning

graph neural networks

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities. This includes talks to attend in person, talks to attend remotely, breaks with colleagues and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).

In order to access this site, you need to register. If you haven't already, please register [here](https://aaai.org/Conferences/AAAI-23/registration/).


AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

technical paper

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

Robot self other distinction active inference meets neural networks learning in a mirror

Minimality of Combined Qualitative Constraint Networks

SI-AGAN: Spatial Interpolation with Attentional Generative Adversarial Networks for Environment Monitoring

You Shouldn’t Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods

Maximal Correlation: An Alternative Criterion for Training Generative Networks

Automated Verification of Social Law Robustness for Reactive Agents

Common and Discriminative Semantic Pursuit for Multi-modal Multi-label Learning

ST-MFM: A Spatiotemporal Multi-modal Fusion Model for Urban Anomalies Prediction

Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization

Semantic Point Completion Network for 3D Semantic Scene Completion

https://d3smihljt9218e.cloudfront.net/transcript/935/subtitle/d49303bb5dc7e55eb0b06fdd70fce71a.vtt

English (automatic)

DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction

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Robot self other distinction active inference meets neural networks learning in a mirror

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DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction

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Next from ECAI 2020

Robot self other distinction active inference meets neural networks learning in a mirror

Similar lecture

Substructure Aware Graph Neural Networks

Downloads