Post #650

GNN User Group Videos 2021 NVIDIA and AWS DGL teams wish you a wonderful Holiday Season and a Happy New Year and to stay connect with their 1,000+ members you can follow their slack channel. You may also watch the replays from our 25 global speakers who made the meetups possible in 2021. • 12/9/2021 Session: Neptune ML: Graph Machine Learning meets Graph Database (Dr. Xiang Song, AWS AI Research and Education Lab & Joy Wang, Amazon Neptune) and Atomistic Line Graph Neural Network for improved materials property predictions (Dr. Kamal Choudhary, National Institute of Standards and Technology (NIST), Maryland). • 10/28/2021 Session: Large-scale GNN training with DGL (Da Zheng Ph.D., Amazon) and New Trends and Results in Graph Federated Learning (Prof. Carl Yang, Emory University). • 9/30/2021 Session: Unified Tensor - Enabling GPU-centric Data Access for Efficient Large Graph GNN Training (Seungwon Min, University of Illinois at Urbana-Champaign) and Challenges and Thinking in Go-production of GNN + DGL (Dr. Jian Zhang, AWS Shanghai AI Lab and AWS Machine Learning Solution Lab). • 7/29/2021 Session: DGL 0.7 release (Dr. Minjie Wang, Amazon), Storing Node Features in GPU memory to speedup billion-scale GNN training (Dr. Dominique LaSalle, NVIDIA), Locally Private Graph Neural Networks (Sina Sajadmanesh, Idiap Research Institute, Switzerland) and Graph Embedding and Application in Meituan (Mengdi Zhang, Meituan). • 6/24/2021 Session: Binary Graph Neural Networks and Dynamic Graph Models (Mehdi Bahri, Imperial College London) and Simplifying large-scale visual analysis of tricky data & models with GPUs, graphs, and ML (Leo Meyerovich, Graphistry Inc). • 5/27/2021 Session: Graphite: GRAPH-Induced feaTure Extraction for Point Cloud Registration (Mahdi Saleh, TUM) Optimizing Graph Transformer Networks with Graph-based Techniques (Loc Hoang, University of Texas at Austin) and Encoding the Core Business Entities Using Meituan Brain (Mengdi Zhang, Meituan). • 4/29/2021 Session: Boost then Convolve: Gradient Boosting Meets Graph Neural Networks (Dr. Sergey Ivanov, Criteo, Russia) and Inductive Representation Learning of Temporal Networks via Causal Anonymous Walks (Prof. Pan Li, Purdue University). • 3/25/2021 Session: Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics (Prof. Marinka Zitnik & Kexin Huang, Harvard University) and The Transformer Network for the Traveling Salesman Problem (Prof. Xavier Bresson, Nanyang Technological University (NTU), Singapore). • 2/25/2021 Session: Gunrock: Graph Analytics on GPU (Dr. John Owens, University of California, Davis), NVIDIA CuGraph - An Open-Source Package for Graphs (Dr. Joe Eaton, NVIDIA) and Exploitation on Learning Mechanism of GNN (Dr. Chuan Shi, Beijing University of Posts and Telecommunications). • 1/28/2021 Session: A Framework For Differentiable Discovery of Graph Algorithms (Dr. Le Song, Georgia Tech).