Schedule

Time Topics Presenter
2017    
July 1, 2017 at 2-3pm PyTorch Chao Shang
July 13, 2017 at 2-3pm TensorFlow Aaron Palmer
July 20, 2017 at 2-3pm Energy-based Generative Adversarial Network Xia Xiao
September 8, 2017 at 2-3pm Semi-Supervised Classification with Graph Convolutional Networks & VIGAN Chao Shang
September 22, 2017 at 1-2pm Discussion of deep learning in drug discovery: Neural Message Passing for Quantum Chemistry Chao Shang
October 6, 2017 at 1-3pm Wasserstein GAN & Towards Principled Methods for Training Generative Adversarial Networks Xia Xiao
October 13, 2017 at 1-3pm Discussion of Learning Convolutional Neural Networks for Graphs Chao Shang
October 20, 2017 at 1:30-3pm Research Discussion Chao Shang
October 27, 2017 at 1:30-3pm Programming for graph convolutional networks Qinqing Liu
November 3, 2017 at 1:30-3pm Understanding deep scattering networks Jin Lu
November 10, 2017 at 1:30-3pm Research Discussion All Members
November 17, 2017 at 1:30-3pm Reinforcement Learning Fei Dou
  Final Weeks Break All Members
2018 Spring    
January 19, 2018 at 1:30-3:30pm Graph Attention Networks Chao Shang
January 26, 2018 at 1:30-3:30pm Discussion All Members
March 2, 2018 at 1:30-3:30pm Monte-Carlo Tree Search Algorithm Tan Zhu
March 9, 2018 at 1:30-3:30pm Poster Competition (ITEB Lobby) All Members
March 16, 2018 at 1:30-3:30pm Discussion All Members
March 23, 2018 at 1:30-3:30pm Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network Xia Xiao
March 30, 2018 at 1:30-2:30pm The rise of deep learning in drug discovery Chao Shang
March 30, 2018 at 2:30-3:30pm Tunneling Neural Perception and Logic Reasoning through Abductive Learning Jin Lu
April 6, 2018 at 1:30-3:30pm Planning chemical syntheses with deep neural networks and symbolic AI (ITEB 217) Chao Shang
April 20, 2018 at 1:30-3:30pm Discussion(ITEB C27) All Members
April 27, 2018 at 1:30-3:30pm Hierarchical Implicit Models and Likelihood-Free Variational Inference  
  Final Weeks Break All Members
2018 Fall    
September 7, 2018 at 4:00-5:00pm Convolutional 2D Knowledge Graph Embeddings Chao Shang
September 14, 2018 at 4:00-5:00pm Latent Space Oddity: on the Curvature of Deep Generative Models Xingyu Cai
September 28, 2018 at 4:00-5:00pm Rethinking statistical learning theory: learning using statistical invariants Jin Lu
October 12, 2018 at 4:00-5:00pm Hierarchical Graph Representation Learning with Differentiable Pooling Chao Shang
October 19, 2018 at 4:00-5:00pm On Kernelized Multi-armed Bandits Tan Zhu
October 26, 2018 at 4:00-5:00pm Escaping Saddles with Stochastic Gradients Guannan Liang
November 2, 2018 at 4:00-5:00pm Dropout as a Bayesian Approximation & Variabtional Dropout & Adversarial Dropout Xia Xiao
November 23, 2018 at 4:00-5:00pm Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Fei Dou
December 7, 2018 at 4:00-5:00pm DropBlock: A regularization method for convolutional networks Zigeng Wang

Location: ITEB 201A

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