Learn to accumulate evidence from all training samples: theory and practice DS Pandey, Q Yu International Conference on Machine Learning, 26963-26989, 2023 | 7 | 2023 |
Evidential conditional neural processes DS Pandey, Q Yu Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9389-9397, 2023 | 7 | 2023 |
Multidimensional belief quantification for label-efficient meta-learning DS Pandey, Q Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data Y Zhu, W Shi, DS Pandey, Y Liu, X Que, DE Krutz, Q Yu 2021 IEEE International Conference on Big Data (Big Data), 1772-1778, 2021 | 3 | 2021 |
Deep temporal sets with evidential reinforced attentions for unique behavioral pattern discovery D Wang, DS Pandey, KP Neupane, Z Yu, E Zheng, Z Zheng, Q Yu International Conference on Machine Learning, 36205-36223, 2023 | 2 | 2023 |
Deep energy-pressure regression for a thermodynamically consistent EOS model D Yu, DS Pandey, J Hinz, D Mihaylov, VV Karasiev, S Hu, Q Yu Machine Learning: Science and Technology, 2024 | 1 | 2024 |
The development of thermodynamically consistent and physics-informed equation-of-state model through machine learning J Hinz, D Yu, DS Pandey, H Sapkota, Q Yu, DI Mihaylov, VV Karasiev, ... APL Machine Learning 2 (2), 2024 | | 2024 |
A Comparative Study of State-of-the-Art Deep Learning Models for Semantic Segmentation of Pores in Scanning Electron Microscope Images of Activated Carbon B Pokharel, DS Pandey, A Sapkota, B Yadav, V Gurung, MP Adhikari, ... IEEE Access 12, 50217-50243, 2024 | | 2024 |