50 citations · 64 across the 6 of their papers we have counts for
6 papers
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Anshul Thakur, Tingting Zhu, Vinayak Abrol +3
The lack of data democratization and information leakage from trained models hinder the development and acceptance of robust deep learning-based healthcare solutions. This paper ar…
Adversarial De-confounding in Individualised Treatment Effects Estimation
Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania +3
Observational studies have recently received significant attention from the machine learning community due to the increasingly available non-experimental observational data and the…
COPER: Continuous Patient State Perceiver
Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue +1
In electronic health records (EHRs), irregular time-series (ITS) occur naturally due to patient health dynamics, reflected by irregular hospital visits, diseases/conditions and the…
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss
Anshul Thakur, Daksh Thapar, Padmanabhan Rajan +1
This paper proposes multiscale convolutional neural network (CNN)-based deep metric learning for bioacoustic classification, under low training data conditions. The proposed CNN is…
Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation
Anshul Thakur, Padmanabhan Rajan
This paper proposes a data-efficient, semi-supervised, two-pass framework for segmenting bird vocalizations. The framework utilizes a binary classification model to categorize fram…
Conv-codes: Audio Hashing For Bird Species Classification
Anshul Thakur, Pulkit Sharma, Vinayak Abrol +1
In this work, we propose a supervised, convex representation based audio hashing framework for bird species classification. The proposed framework utilizes archetypal analysis, a m…