122 citations · 155 across the 14 of their papers we have counts for
8 papers · 1 filter
A General Purpose Neural Architecture for Geospatial Systems
Nasim Rahaman, Martin Weiss, Frederik Träuble +6
Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to support a wide variety of important applications. H…
Neural Attentive Circuits
Nasim Rahaman, Martin Weiss, Francesco Locatello +5
Recent work has seen the development of general purpose neural architectures that can be trained to perform tasks across diverse data modalities. General purpose models typically m…
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…
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…
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…
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…