Follow
Ashwini Pokle
Ashwini Pokle
PhD Student in Machine Learning, Carnegie Mellon University
Verified email at andrew.cmu.edu - Homepage
Title
Cited by
Cited by
Year
Deep local trajectory replanning and control for robot navigation
A Pokle, R Martín-Martín, P Goebel, V Chow, HM Ewald, J Yang, Z Wang, ...
2019 international conference on robotics and automation (ICRA), 5815-5822, 2019
872019
Translating navigation instructions in natural language to a high-level plan for behavioral robot navigation
X Zang, A Pokle, M Vázquez, K Chen, JC Niebles, A Soto, S Savarese
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
382018
Deep equilibrium approaches to diffusion models
A Pokle, Z Geng, JZ Kolter
Advances in Neural Information Processing Systems 35, 37975-37990, 2022
342022
Contrasting the landscape of contrastive and non-contrastive learning
A Pokle, J Tian, Y Li, A Risteski
25th International Conference on Artificial Intelligence and Statistics …, 2022
342022
One-step diffusion distillation via deep equilibrium models
Z Geng, A Pokle, JZ Kolter
Advances in Neural Information Processing Systems 36, 41914-41931, 2023
262023
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
C Anil, A Pokle, K Liang, J Treutlein, Y Wu, S Bai, Z Kolter, R Grosse
Advances in Neural Information Processing Systems 35, 7796-7809., 2022
252022
Consistency models made easy
Z Geng, A Pokle, W Luo, J Lin, JZ Kolter
arXiv preprint arXiv:2406.14548, 2024
182024
Training-free linear image inverses via flows
A Pokle, MJ Muckley, RTQ Chen, B Karrer
Transactions on Machine Learning Research, 2023
17*2023
Deep equilibrium based neural operators for steady-state pdes
T Marwah, A Pokle, JZ Kolter, Z Lipton, J Lu, A Risteski
Advances in Neural Information Processing Systems 36, 15716-15737, 2023
62023
Visually-grounded library of behaviors for manipulating diverse objects across diverse configurations and views
J Yang, HY Tung, Y Zhang, G Pathak, A Pokle, CG Atkeson, K Fragkiadaki
5th Annual Conference on Robot Learning, 2021
12021
Differentially Private Generation of High Fidelity Samples From Diffusion Models
V Sehwag, A Panda, A Pokle, X Tang, S Mahloujifar, M Chiang, JZ Kolter, ...
The system can't perform the operation now. Try again later.
Articles 1–11