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Rohit Sonker

3 accepted papers

2025

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks

ICML 2025poster

Machine learning algorithms often struggle to control complex real-world systems. In the case of nuclear fusion, these challenges are exacerbated, as the dynamics are notoriously complex, data is poor, hardware is subject to failures, and experiments often affect dynamics beyond the experiment's dur…

Cited by 0SourcePDFScholar
2022

Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios

ICLR 2022poster

Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and for system identification. However, these models are often based on the assumption that the dynamics are fixed and unchanging, which is rarely the case in real-world scenarios. Many contro…

2021

Adding Terrain Height to Improve Model Learning for Path Tracking on Uneven Terrain by a Four Wheel Robot

RA-L 2021

Closely tracking a defined path by a wheeled mobile robot on a three-dimensional surface is important for accurate movement on uneven terrain. Conventional methods in two dimensions are difficult to extend to three dimensions due to the computational complexity in finding wheel-terrain interactions.

Cited by 18SourceScholar