5 citations · 9 across the 4 of their papers we have counts for
4 papers
Learning Label Encodings for Deep Regression
Deval Shah, Tor M. Aamodt
Deep regression networks are widely used to tackle the problem of predicting a continuous value for a given input. Task-specialized approaches for training regression networks have…
Label Encoding for Regression Networks
Deval Shah, Zi Yu Xue, Tor M. Aamodt
Deep neural networks are used for a wide range of regression problems. However, there exists a significant gap in accuracy between specialized approaches and generic direct regress…
Characterizing and Improving the Resilience of Accelerators in Autonomous Robots
Deval Shah, Zi Yu Xue, Karthik Pattabiraman +1
Motion planning is a computationally intensive and well-studied problem in autonomous robots. However, motion planning hardware accelerators (MPA) must be soft-error resilient for…
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator
Jonathan Lew, Deval Shah, Suchita Pati +8
Most deep neural networks deployed today are trained using GPUs via high-level frameworks such as TensorFlow and PyTorch. This paper describes changes we made to the GPGPU-Sim simu…