72 citations · 178 across the 12 of their papers we have counts for
17 papers
Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning
Ivaxi Sheth, Aamer Abdul Rahman, Mohammad Havaei +1
Humans have perfected the art of learning from multiple modalities through sensory organs. Despite their impressive predictive performance on a single modality, neural networks can…
BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning
Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi +3
Current pre-trained language models rely on large datasets for achieving state-of-the-art performance. However, past research has shown that not all examples in a dataset are equal…
Automatic Evaluation of Excavator Operators using Learned Reward Functions
Pranav Agarwal, Marek Teichmann, Sheldon Andrews +1
Training novice users to operate an excavator for learning different skills requires the presence of expert teachers. Considering the complexity of the problem, it is comparatively…
Learning Latent Structural Causal Models
Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth +5
Causal learning has long concerned itself with the accurate recovery of underlying causal mechanisms. Such causal modelling enables better explanations of out-of-distribution data.…
Learning Robust Dynamics through Variational Sparse Gating
Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi +3
Learning world models from their sensory inputs enables agents to plan for actions by imagining their future outcomes. World models have previously been shown to improve sample-eff…
Simple Video Generation using Neural ODEs
David Kanaa, Vikram Voleti, Samira Ebrahimi Kahou +1
Despite having been studied to a great extent, the task of conditional generation of sequences of frames, or videos, remains extremely challenging. It is a common belief that a key…