activity
20182021
most citedA Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

122 citations · 151 across the 6 of their papers we have counts for

collaborators

10 papers

cs.LG20219 cited

Dynamic Inference with Neural Interpreters

Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi +4

Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution. However, they are less capable of systematic generalizat…

cs.CY20202 cited

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing

Prateek Gupta, Tegan Maharaj, Martin Weiss +26

The rapid global spread of COVID-19 has led to an unprecedented demand for effective methods to mitigate the spread of the disease, and various digital contact tracing (DCT) method…

cs.LG2020

Predicting Infectiousness for Proactive Contact Tracing

Yoshua Bengio, Prateek Gupta, Tegan Maharaj +20

The COVID-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries and resulting in widespread lockdowns for emergency containment. Large-sca…

cs.LG2020

Function Contrastive Learning of Transferable Meta-Representations

Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman +3

Meta-learning algorithms adapt quickly to new tasks that are drawn from the same task distribution as the training tasks. The mechanism leading to fast adaptation is the conditioni…

cs.LG20208 cited

S2RMs: Spatially Structured Recurrent Modules

Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal +5

Capturing the structure of a data-generating process by means of appropriate inductive biases can help in learning models that generalize well and are robust to changes in the inpu…

cs.CR20209 cited

COVI White Paper

Hannah Alsdurf, Edmond Belliveau, Yoshua Bengio +21

The SARS-CoV-2 (Covid-19) pandemic has caused significant strain on public health institutions around the world. Contact tracing is an essential tool to change the course of the Co…