Timezone: »
Panel
Vikas Garg · Pan Li · Srijan Kumar · Emanuele Rossi · Shenyang Huang
Author Information
Vikas Garg (Aalto University/YaiYai Ltd)
Pan Li (Purdue University)
Srijan Kumar (Georgia Institute of Technology)
Emanuele Rossi (Imperial College London)
Shenyang Huang (McGill University, Mila)
I am a phd student at Mila and McGill University, supervised by Professor Reihaneh Rabbany and Professor Guillaume Rabusseau.
More from the Same Authors
-
2021 : Few Shot Image Generation via Implicit Autoencoding of Support Sets »
Shenyang Huang · Kuan-Chieh Wang · Guillaume Rabusseau · Alireza Makhzani -
2022 : Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph Models »
Kartik Sharma · Rakshit Trivedi · Rohit Sridhar · Srijan Kumar -
2022 : Interpretable Geometric Deep Learning via Learnable Randomness Injection »
Siqi Miao · Yunan Luo · Mia Liu · Pan Li -
2022 : Provably Efficient Causal Model-Based Reinforcement Learning for Environment-Agnostic Generalization »
Mirco Mutti · Riccardo De Santi · Emanuele Rossi · Juan Calderon · Michael Bronstein · Marcello Restelli -
2022 : Modular Flows: Differential Molecular Generation »
Yogesh Verma · Samuel Kaski · Markus Heinonen · Vikas Garg -
2022 : Provably expressive temporal graph networks »
Amauri Souza · Diego Mesquita · Samuel Kaski · Vikas Garg -
2022 : Modular Flows: Differential Molecular Generation »
Yogesh Verma · Samuel Kaski · Markus Heinonen · Vikas Garg -
2022 : On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs with Missing Node Features »
Emanuele Rossi · Henry Kenlay · Maria Gorinova · Benjamin Chamberlain · Xiaowen Dong · Michael Bronstein -
2022 Spotlight: Are GANs overkill for NLP? »
David Alvarez-Melis · Vikas Garg · Adam Kalai -
2022 : KeyNote 5 by Pan Li: Representation learning for predicting temporal network evolution »
Pan Li -
2022 : KeyNote 4 by Srijan Kumar: Temporal GNNs for Web Safety and Integrity »
Srijan Kumar -
2022 : KeyNote 3 by Vikas Garg: Provably Powerful Temporal Graph Networks »
Vikas Garg -
2022 : Spotlight: Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph Models »
Kartik Sharma · Rakshit Trivedi · Rohit Sridhar · Srijan Kumar -
2022 Workshop: Temporal Graph Learning Workshop »
Reihaneh Rabbany · Jian Tang · Michael Bronstein · Shenyang Huang · Meng Qu · Kellin Pelrine · Jianan Zhao · Farimah Poursafaei · Aarash Feizi -
2022 Poster: Modular Flows: Differential Molecular Generation »
Yogesh Verma · Samuel Kaski · Markus Heinonen · Vikas Garg -
2022 Poster: Are GANs overkill for NLP? »
David Alvarez-Melis · Vikas Garg · Adam Kalai -
2022 Poster: Symmetry-induced Disentanglement on Graphs »
Giangiacomo Mercatali · Andre Freitas · Vikas Garg -
2022 Poster: Towards Better Evaluation for Dynamic Link Prediction »
Farimah Poursafaei · Shenyang Huang · Kellin Pelrine · Reihaneh Rabbany -
2022 Poster: Provably expressive temporal graph networks »
Amauri Souza · Diego Mesquita · Samuel Kaski · Vikas Garg -
2021 : GRAND: Graph Neural Diffusion »
Benjamin Chamberlain · James Rowbottom · Maria Gorinova · Stefan Webb · Emanuele Rossi · Michael Bronstein -
2020 Poster: Graph Information Bottleneck »
Tailin Wu · Hongyu Ren · Pan Li · Jure Leskovec -
2020 Poster: Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning »
Pan Li · Yanbang Wang · Hongwei Wang · Jure Leskovec -
2019 Poster: Solving graph compression via optimal transport »
Vikas Garg · Tommi Jaakkola -
2019 Poster: Generative Models for Graph-Based Protein Design »
John Ingraham · Vikas Garg · Regina Barzilay · Tommi Jaakkola -
2019 Poster: Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms »
Vikas Garg · Tamar Pichkhadze -
2018 Poster: Learning SMaLL Predictors »
Vikas Garg · Ofer Dekel · Lin Xiao -
2018 Poster: Supervising Unsupervised Learning »
Vikas Garg · Adam Kalai -
2018 Spotlight: Supervising Unsupervised Learning »
Vikas Garg · Adam Kalai -
2016 Poster: Learning Tree Structured Potential Games »
Vikas Garg · Tommi Jaakkola