Search Results for author: Akash Haridas

Found 2 papers, 1 papers with code

DADAgger: Disagreement-Augmented Dataset Aggregation

no code implementations3 Jan 2023 Akash Haridas, Karim Hamadeh, Samarendra Chandan Bindu Dash

DAgger is an imitation algorithm that aggregates its original datasets by querying the expert on all samples encountered during training.

Car Racing

Deep Neural Networks to Correct Sub-Precision Errors in CFD

2 code implementations9 Feb 2022 Akash Haridas, Nagabhushana Rao Vadlamani, Yuki Minamoto

In particular, errors related to numerical precision ("sub-precision errors") can accumulate in the quantities of interest when the simulations are performed using low-precision 16-bit floating-point arithmetic compared to an equivalent 64-bit simulation.

Cannot find the paper you are looking for? You can Submit a new open access paper.