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2020 – today
- 2025
[j2]Wenqing Zheng, S. P. Sharan, Zhiwen Fan, Kevin Wang, Yihan Xi, Zhangyang Wang:
Symbolic Visual Reinforcement Learning: A Scalable Framework With Object-Level Abstraction and Differentiable Expression Search. IEEE Trans. Pattern Anal. Mach. Intell. 47(1): 400-412 (2025)- 2024
- [i5]S. P. Sharan, Francesco Pittaluga, Vijay Kumar B. G, Manmohan Chandraker:
LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning. CoRR abs/2401.00125 (2024) - 2023
- [j1]Mobarakol Islam, Lalithkumar Seenivasan
, S. P. Sharan, V. K. Viekash, Bhavesh Gupta, Ben Glocker, Hongliang Ren:
Paced-curriculum distillation with prediction and label uncertainty for image segmentation. Int. J. Comput. Assist. Radiol. Surg. 18(10): 1875-1883 (2023) - [c3]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. ICML 2023: 42403-42419 - [i4]Mobarakol Islam, Lalithkumar Seenivasan, S. P. Sharan, V. K. Viekash, Bhavesh Gupta, Ben Glocker, Hongliang Ren:
Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation. CoRR abs/2302.01049 (2023) - [i3]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. CoRR abs/2305.00909 (2023) - 2022
- [c2]S. P. Sharan, Adithya K. Krishna, A. Siddharth Rao, Varun P. Gopi:
RepAr-Net: Re-Parameterized Encoders and Attentive Feature Arsenals for Fast Video Denoising. ICRA 2022: 633-639 - [c1]S. P. Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang:
Symbolic Distillation for Learned TCP Congestion Control. NeurIPS 2022 - [i2]S. P. Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang:
Symbolic Distillation for Learned TCP Congestion Control. CoRR abs/2210.16987 (2022) - [i1]Wenqing Zheng, S. P. Sharan, Zhiwen Fan, Kevin Wang, Yihan Xi, Zhangyang Wang:
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search. CoRR abs/2212.14849 (2022)
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