69 citations · 194 across the 10 of their papers we have counts for
11 papers
GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs
Marios Papachristou, Rishab Goel, Frank Portman +2
In graph learning, there have been two predominant inductive biases regarding graph-inspired architectures: On the one hand, higher-order interactions and message passing work well…
Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning
Arsene Fansi Tchango, Rishab Goel, Julien Martel +3
The automation of the medical evidence acquisition and diagnosis process has recently attracted increasing attention in order to reduce the workload of doctors and democratize acce…
DDXPlus: A New Dataset For Automatic Medical Diagnosis
Arsene Fansi Tchango, Rishab Goel, Zhi Wen +2
There has been a rapidly growing interest in Automatic Symptom Detection (ASD) and Automatic Diagnosis (AD) systems in the machine learning research literature, aiming to assist do…
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions
David Bieber, Rishab Goel, Daniel Zheng +2
The execution behavior of a program often depends on external resources, such as program inputs or file contents, and so cannot be run in isolation. Nevertheless, software develope…
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel +3
While deep reinforcement learning excels at solving tasks where large amounts of data can be collected through virtually unlimited interaction with the environment, learning from l…
Out-of-Sample Representation Learning for Multi-Relational Graphs
Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi
Many important problems can be formulated as reasoning in knowledge graphs. Representation learning has proved extremely effective for transductive reasoning, in which one needs to…