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ORCIDAnshul Thakur
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j9]Soheila Molaei, Nima Ghanbari Bousejin, Ghadeer O. Ghosheh, Anshul Thakur, Vinod Kumar Chauhan
, Tingting Zhu, David A. Clifton:
CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks. J. Heal. Informatics Res. 8(3): 555-575 (2024)- [j8]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, Omid Rohanian, Soheila Molaei, David A. Clifton:
Continuous patient state attention model for addressing irregularity in electronic health records. BMC Medical Informatics Decis. Mak. 24(1): 117 (2024) - [j7]Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Tingting Zhu, David A. Clifton:
Incremental Trainable Parameter Selection in Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6478-6491 (2024) - [c21]Soheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew A. S. Soltan, Hadi Zare, David A. Clifton:
Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks. AISTATS 2024: 1342-1350 - [c20]Fenglin Liu, Zheng Li, Hongjian Zhou, Qingyu Yin, Jingfeng Yang, Xianfeng Tang, Chen Luo, Ming Zeng, Haoming Jiang, Yifan Gao, Priyanka Nigam, Sreyashi Nag, Bing Yin, Yining Hua, Xuan Zhou, Omid Rohanian, Anshul Thakur, Lei A. Clifton, David A. Clifton:
Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark. EMNLP 2024: 13696-13710 - [c19]Shantanu Singh Baliyan, Anshul Thakur, Laxmeesha Somappa:
On-chip Data Compression Techniques for High-Density Implantable Neural Recording. ISCAS 2024: 1-5 - 2023
- [j6]Anshul Thakur, Jacob Armstrong, Alexey Youssef, David W. Eyre, David A. Clifton:
Self-Aware SGD: Reliable Incremental Adaptation Framework for Clinical AI Models. IEEE J. Biomed. Health Informatics 27(3): 1624-1634 (2023) - [c18]Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton:
Adversarial De-confounding in Individualised Treatment Effects Estimation. AISTATS 2023: 837-849 - [i8]Alexey Youssef, Michael Pencina, Anshul Thakur, Tingting Zhu, David A. Clifton, Nigam H. Shah:
All models are local: time to replace external validation with recurrent local validation. CoRR abs/2305.03219 (2023) - [i7]Anshul Thakur, Tingting Zhu, Vinayak Abrol, Jacob Armstrong, Yujiang Wang, David A. Clifton:
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention. CoRR abs/2305.03710 (2023) - [i6]Yujiang Wang, Anshul Thakur, Mingzhi Dong, Pingchuan Ma, Stavros Petridis, Li Shang, Tingting Zhu, David A. Clifton:
Is dataset condensation a silver bullet for healthcare data sharing? CoRR abs/2305.03711 (2023) - 2022
- [j5]Anshul Thakur, Pulkit Sharma, David A. Clifton:
Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications. IEEE J. Biomed. Health Informatics 26(4): 1761-1772 (2022) - [j4]Anshul Thakur, Swades De:
On Deploying Secondary Networks in Co-Channel Bands with DTV Networks. IEEE Trans. Veh. Technol. 71(7): 7791-7804 (2022) - [c17]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton:
COPER: Continuous Patient State Perceiver. BHI 2022: 1-4 - [c16]Anshul Thakur, Vinayak Abrol, Pulkit Sharma:
Does Geometric Structure in Convolutional Filter Space Provide Filter Redundancy Information? NeurReps 2022: 111-121 - [i5]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton:
COPER: Continuous Patient State Perceiver. CoRR abs/2208.03196 (2022) - [i4]Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton:
Adversarial De-confounding in Individualised Treatment Effects Estimation. CoRR abs/2210.10530 (2022) - 2020
- [j3]Anshul Thakur, Swades De, Gabriel-Miro Muntean:
Co-Channel Secondary Deployment Over DTV Bands Using Reconfigurable Radios. IEEE Trans. Veh. Technol. 69(10): 12202-12215 (2020) - [c15]Krati Gupta, Anshul Thakur, Michael H. Goldbaum, Siamak Yousefi:
Glaucoma Precognition: Recognizing Preclinical Visual Functional Signs of Glaucoma. CVPR Workshops 2020: 4393-4401
2010 – 2019
- 2019
- [j2]Anshul Thakur, Padmanabhan Rajan:
Deep Archetypal Analysis Based Intermediate Matching Kernel for Bioacoustic Classification. IEEE J. Sel. Top. Signal Process. 13(2): 298-309 (2019) - [c14]Anshul Thakur, Pulkit Sharma, Vinayak Abrol, Padmanabhan Rajan:
CONV-codes: Audio Hashing for Bird Species Classification. ICASSP 2019: 8241-8245 - [c13]Anshul Thakur, Swades De, Gabriel-Miro Muntean:
Interference-Aware Co-Channel Transmission Over DTV Bands via Partial Frequency and Time Overlaps. ICC 2019: 1-6 - [i3]Anshul Thakur, Pulkit Sharma, Vinayak Abrol, Padmanabhan Rajan:
Conv-codes: Audio Hashing For Bird Species Classification. CoRR abs/1902.02498 (2019) - [i2]Anshul Thakur, Padmanabhan Rajan:
Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation. CoRR abs/1902.09765 (2019) - [i1]Anshul Thakur, Daksh Thapar, Padmanabhan Rajan, Aditya Nigam:
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss. CoRR abs/1903.10713 (2019) - 2018
- [c12]Arshdeep Singh, Anshul Thakur, Padmanabhan Rajan, Arnav Bhavsar:
A Layer-wise Score Level Ensemble Framework for Acoustic Scene Classification. EUSIPCO 2018: 837-841 - [c11]Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Padmanabhan Rajan:
Compressed Convex Spectral Embedding for Bird Species Classification. ICASSP 2018: 261-265 - [c10]Arjun Pankajakshan, Anshul Thakur, Daksh Thapar, Padmanabhan Rajan, Aditya Nigam:
All-Conv Net for Bird Activity Detection: Significance of Learned Pooling. INTERSPEECH 2018: 2122-2126 - [c9]Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Padmanabhan Rajan:
Deep Convex Representations: Feature Representations for Bioacoustics Classification. INTERSPEECH 2018: 2127-2131 - [c8]Pulkit Sharma, Vinayak Abrol, Anshul Thakur:
ASe: Acoustic Scene Embedding Using Deep Archetypal Analysis and GMM. INTERSPEECH 2018: 3299-3303 - [c7]Arshdeep Singh, Anshul Thakur, Padmanabhan Rajan:
APE: Archetypal-Prototypal Embeddings for Audio Classification. MLSP 2018: 1-6 - [c6]Anshul Thakur, Arshdeep Singh, Padmanabhan Rajan:
Convex likelihood alignments for bioacoustic Classification. MLSP 2018: 1-6 - 2017
- [c5]Anshul Thakur, R. Jyothi, Padmanabhan Rajan, Aroor Dinesh Dileep:
Rapid bird activity detection using probabilistic sequence kernels. EUSIPCO 2017: 1754-1758 - [c4]Vinayak Abrol, Pulkit Sharma, Anshul Thakur, Padmanabhan Rajan, Aroor Dinesh Dileep, Anil Kumar Sao:
Archetypal analysis based sparse convex sequence kernel for bird activity detection. EUSIPCO 2017: 1774-1778 - [c3]Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Padmanabhan Rajan:
Rényi entropy based mutual information for semi-supervised bird vocalization segmentation. MLSP 2017: 1-6 - [c2]Anshul Thakur, Padmanabhan Rajan:
Unsupervised birdcall activity detection using source and system features. NCC 2017: 1-6 - 2016
- [c1]Anshul Thakur, Padmanabhan Rajan:
Model-based unsupervised segmentation of birdcalls from field recordings. ICSPCS 2016: 1-6 - 2015
- [j1]Shailendra Singh, Anshul Thakur, Dharam Vir:
Automatic articulation error detection tool for Punjabi language with aid for hearing impaired people. Int. J. Speech Technol. 18(2): 143-156 (2015)
Coauthor Index
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