Wavelet Decomposition Based Automatic Sleep Stage Classification Using EEG. - Nieves Crasto; Richa Upadhyay (IWBBIO (1), 2017)

Imagined Object Recognition Using EEG-Based Neurological Brain Signals. - Rajkumar Saini; Sameer Prabhu; Richa Upadhyay; Sumit Rakesh; Prakash Chandra Chhipa; Hamam Mokayed; Marcus Liwicki; Foteini Liwicki (RTIP2R, 2021)

Sharing to learn and learning to share - Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning : A meta review. - Richa Upadhyay; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (CoRR, 2021)

Emotions Classification Using EEG in Health Care. - Sumit Rakesh; Foteini Liwicki; Hamam Mokayed; Richa Upadhyay; Prakash Chandra Chhipa; Vibha Gupta; Kanjar De; György Kovács 001; Dinesh Singh; Rajkumar Saini (CVMI, 2022)

Investigating the Effect of Using Synthetic and Semi-synthetic Images for Historical Document Font Classification. - Konstantina Nikolaidou; Richa Upadhyay; Mathias Seuret; Marcus Liwicki (DAS, 2022)

Depth Contrast: Self-supervised Pretraining on 3DPM Images for Mining Material Classification. - Prakash Chandra Chhipa; Richa Upadhyay; Rajkumar Saini; Lars Lindqvist; Richard Nordenskjöld; Seiichi Uchida; Marcus Liwicki (ECCV Workshops (7), 2022)

Deep Neural Network approaches for Analysing Videos of Music Performances. - Foteini Simistira Liwicki; Richa Upadhyay; Prakash Chandra Chhipa; Killian Murphy; Federico Visi; Stefan Östersjö; Marcus Liwicki (CoRR, 2022)

Functional Knowledge Transfer with Self-supervised Representation Learning. - Prakash Chandra Chhipa; Muskaan Chopra; Gopal Mengi; Varun Gupta 005; Richa Upadhyay; Meenakshi Subhash Chippa; Kanjar De; Rajkumar Saini; Seiichi Uchida; Marcus Liwicki (ICIP, 2023)

Multi-Task Meta Learning: learn how to adapt to unseen tasks. - Richa Upadhyay; Prakash Chandra Chhipa; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (IJCNN, 2023)

Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images. - Prakash Chandra Chhipa; Richa Upadhyay; Gustav Grund Pihlgren; Rajkumar Saini; Seiichi Uchida; Marcus Liwicki (WACV, 2023)

Less is More - Towards parsimonious multi-task models using structured sparsity. - Richa Upadhyay; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (CPAL, 2024)

Giving Each Task what it Needs Leveraging Structured Sparsity for Tailored Multi-Task Learning. - Richa Upadhyay; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (ECCV Workshops (11), 2024)

An EEG Analysis Framework for Brain Disorder Classification Using Convolved Connectivity Features. - Rajkumar Saini; Richa Upadhyay; Vibha Gupta; Prakash Chandra Chhipa; Sumit Rakesh; Hamam Mokayed; Kanjar De; Foteini Simistira Liwicki; Debashis Das Chakladar (ICFSP, 2024)

Sharing to Learn and Learning to Share; Fitting Together Meta, Multi-Task, and Transfer Learning: A Meta Review. - Richa Upadhyay; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (IEEE Access, 2024)

Sharing to Learn and Learning to Share: Meta-learning to Enhance Multi-task Learning. - Richa Upadhyay (2025)

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning. - Richa Upadhyay; Ronald Phlypo; Rajkumar Saini; Marcus Liwicki (CoRR, 2025)