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ORCIDNishant Jain
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2020 – today
- 2024
[j8]Pragya Gupta, Nishant Jain
:
Anisotropic diffusion filter based fusion of NSST transformed medical images. Biomed. Signal Process. Control. 90: 105819 (2024)- [j7]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Learning Robust Multi-scale Representation for Neural Radiance Fields from Unposed Images. Int. J. Comput. Vis. 132(4): 1310-1335 (2024) - [c14]Nishant Jain, Pradeep Shenoy:
Instance-Conditional Timescales of Decay for Non-Stationary Learning. AAAI 2024: 12773-12781 - [c13]Nishant Jain, Arun S. Suggala, Pradeep Shenoy:
Improving Generalization via Meta-Learning on Hard Samples. CVPR 2024: 27590-27599 - [c12]Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy:
Learning model uncertainty as variance-minimizing instance weights. ICLR 2024 - [i12]Nishant Jain, Arun S. Suggala, Pradeep Shenoy:
Improving Generalization via Meta-Learning on Hard Samples. CoRR abs/2403.12236 (2024) - [i11]Brian Coyle, El Amine Cherrat, Nishant Jain, Natansh Mathur, Snehal Raj, Skander Kazdaghli, Iordanis Kerenidis:
Training-efficient density quantum machine learning. CoRR abs/2405.20237 (2024) - 2023
- [j6]Nishant Jain, Prasanta K. Jana:
LRF: A logically randomized forest algorithm for classification and regression problems. Expert Syst. Appl. 213(Part): 119225 (2023) - [c11]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Enhanced Stable View Synthesis. CVPR 2023: 13208-13217 - [c10]Nishant Jain, Harkirat S. Behl, Yogesh Singh Rawat, Vibhav Vineet:
Efficiently Robustify Pre-Trained Models. ICCV 2023: 5482-5492 - [i10]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Enhanced Stable View Synthesis. CoRR abs/2303.17094 (2023) - [i9]Nishant Jain, Harkirat S. Behl, Yogesh Singh Rawat, Vibhav Vineet:
Efficiently Robustify Pre-trained Models. CoRR abs/2309.07499 (2023) - [i8]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images. CoRR abs/2311.04521 (2023) - 2022
- [j5]Nishant Jain, Prasanta K. Jana:
XRRF: An eXplainable Reasonably Randomised Forest algorithm for classification and regression problems. Inf. Sci. 613: 139-160 (2022) - [j4]Nishant Jain, Brian Coyle, Elham Kashefi, Niraj Kumar:
Graph neural network initialisation of quantum approximate optimisation. Quantum 6: 861 (2022) - [c9]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Robustifying the Multi-Scale Representation of Neural Radiance Fields. BMVC 2022: 578 - [c8]Donglai Wei, Siddhant Kharbanda, Sarthak Arora, Roshan Roy, Nishant Jain, Akash Palrecha, Tanav Shah, Shray Mathur, Ritik Mathur, Abhijay Kemkar, Anirudh Srinivasan Chakravarthy, Zudi Lin, Won-Dong Jang, Yansong Tang, Song Bai, James Tompkin, Philip H. S. Torr, Hanspeter Pfister:
YouMVOS: An Actor-centric Multi-shot Video Object Segmentation Dataset. CVPR 2022: 21012-21021 - [i7]Nishant Jain, Suryansh Kumar, Luc Van Gool:
Robustifying the Multi-Scale Representation of Neural Radiance Fields. CoRR abs/2210.04233 (2022) - [i6]Nishant Jain, Pradeep Shenoy:
Learning on non-stationary data with re-weighting. CoRR abs/2212.05908 (2022) - [i5]Nishant Jain, Pradeep Shenoy:
Selective classification using a robust meta-learning approach. CoRR abs/2212.05987 (2022) - 2021
- [j3]Nishant Jain, Abhinav Tomar, Prasanta K. Jana:
A novel scheme for employee churn problem using multi-attribute decision making approach and machine learning. J. Intell. Inf. Syst. 56(2): 279-302 (2021) - [c7]Nishant Jain, Iris Zachary, Suzanne Austin Boren:
Who Influences Cancer Conversations on Twitter?: A Comparative Surveillance of Cancer Communications. MedInfo 2021: 719-723 - [i4]Nishant Jain, Brian Coyle, Elham Kashefi, Niraj Kumar:
Graph neural network initialisation of quantum approximate optimisation. CoRR abs/2111.03016 (2021) - 2020
- [c6]Uppugunduru Anil Kumar, Nishant Jain, Sumit K. Chatterjee, Syed Ershad Ahmed:
Evaluation of Multiplier-Less DCT Transform Using In-Exact Computing. MIND (2) 2020: 11-23
2010 – 2019
- 2019
- [c5]Suraj Tripathi, Chirag Singh, Abhay Kumar, Chandan Kumar Pandey, Nishant Jain:
Bidirectional Transformer Based Multi-Task Learning for Natural Language Understanding. NLDB 2019: 54-65 - [c4]Nishant Jain, Abhay Kumar, Shekhar Singh, Chirag Singh, Suraj Tripathi:
Deceptive Reviews Detection Using Deep Learning Techniques. NLDB 2019: 79-91 - [i3]Abhay Kumar, Nishant Jain, Chirag Singh, Suraj Tripathi:
Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network. CoRR abs/1904.00197 (2019) - [i2]Abhay Kumar, Nishant Jain, Suraj Tripathi, Chirag Singh:
From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation. CoRR abs/1906.04914 (2019) - [i1]Abhay Kumar, Nishant Jain, Suraj Tripathi, Chirag Singh, Kamal Krishna:
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation. CoRR abs/1908.08652 (2019) - 2018
- [c3]Nishant Jain, Abhinav Tomar, Prasanta K. Jana:
Novel Framework for Performance Prediction of Small and Medium Scale Enterprises: A Machine Learning Approach. ICACCI 2018: 42-47 - [c2]Nishant Jain, Xiaozhe Fan, Walter Daniel Leon-Salas, Anne M. Lucietto:
Extending battery life of smartphones by overcoming idle power consumption using ambient light energy harvesting. ICIT 2018: 978-983 - 2017
- [j2]Nishant Jain, Vinod Kumar:
Liver Ultrasound Image Segmentation Using Region-Difference Filters. J. Digit. Imaging 30(3): 376-390 (2017) - 2016
- [j1]Nishant Jain, Vinod Kumar:
IFCM Based Segmentation Method for Liver Ultrasound Images. J. Medical Syst. 40(11): 249:1-249:12 (2016) - 2013
- [c1]Kshitiz Bakhshi, Nishant Jain, Pushpendra Singh, Arjun Ahuja:
MoSen: a middleware for mobile sensor programming. ACM DEV (3) 2013: 31:1-31:2
Coauthor Index
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last updated on 2024-10-08 20:34 CEST by the dblp team
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