2k citations · 2k across the 7 of their papers we have counts for
9 papers
Comparative Analysis of Diffusion Generative Models in Computational Pathology
Denisha Thakkar, Vincent Quoc-Huy Trinh, Sonal Varma +3
Diffusion Generative Models (DGM) have rapidly surfaced as emerging topics in the field of computer vision, garnering significant interest across a wide array of deep learning appl…
KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
Rambod Azimi, Rishav Rishav, Marek Teichmann +1
Large language models (LLMs) have demonstrated remarkable performance across various downstream tasks. However, the high computational and memory requirements of LLMs are a major b…
Empowering Clinicians with Medical Decision Transformers: A Framework for Sepsis Treatment
Aamer Abdul Rahman, Pranav Agarwal, Rita Noumeir +3
Offline reinforcement learning has shown promise for solving tasks in safety-critical settings, such as clinical decision support. Its application, however, has been limited by the…
Learning to Play Atari in a World of Tokens
Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou
Model-based reinforcement learning agents utilizing transformers have shown improved sample efficiency due to their ability to model extended context, resulting in more accurate wo…
Auxiliary Losses for Learning Generalizable Concept-based Models
Ivaxi Sheth, Samira Ebrahimi Kahou
The increasing use of neural networks in various applications has lead to increasing apprehensions, underscoring the necessity to understand their operations beyond mere final pred…
Transformers in Reinforcement Learning: A Survey
Pranav Agarwal, Aamer Abdul Rahman, Pierre-Luc St-Charles +2
Transformers have significantly impacted domains like natural language processing, computer vision, and robotics, where they improve performance compared to other neural networks.…