53 citations · 120 across the 12 of their papers we have counts for
12 papers
A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
Ihab Bendidi, Yassir El Mesbahi, Alisandra K. Denton +4
Understanding cellular responses to stimuli is crucial for biological discovery and drug development. Transcriptomics provides interpretable, gene-level insights, while microscopy…
How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval
Philip Fradkin, Puria Azadi, Karush Suri +4
Predicting molecular impact on cellular function is a core challenge in therapeutic design. Phenomic experiments, designed to capture cellular morphology, utilize microscopy based…
On the Scalability of GNNs for Molecular Graphs
Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei +4
Scaling deep learning models has been at the heart of recent revolutions in language modelling and image generation. Practitioners have observed a strong relationship between model…
TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade Execution
Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis +1
Advances in Reinforcement Learning (RL) span a wide variety of applications which motivate development in this area. While application tasks serve as suitable benchmarks for real w…
Energy-based Surprise Minimization for Multi-Agent Value Factorization
Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis +1
Multi-Agent Reinforcement Learning (MARL) has demonstrated significant success in training decentralised policies in a centralised manner by making use of value factorization metho…
Maximum Mutation Reinforcement Learning for Scalable Control
Karush Suri, Xiao Qi Shi, Konstantinos N. Plataniotis +1
Advances in Reinforcement Learning (RL) have demonstrated data efficiency and optimal control over large state spaces at the cost of scalable performance. Genetic methods, on the o…
Transfer Learning for sEMG-based Hand Gesture Classification using Deep Learning in a Master-Slave Architecture
Karush Suri, Rinki Gupta
Recent advancements in diagnostic learning and development of gesture-based human machine interfaces have driven surface electromyography (sEMG) towards significant importance. Ana…
Dual Stage Classification of Hand Gestures using Surface Electromyogram
Karush Suri, Rinki Gupta
Surface electromyography (sEMG) is becoming exceeding useful in applications involving analysis of human motion such as in human-machine interface, assistive technology, healthcare…
Classification of Hand Gestures from Wearable IMUs using Deep Neural Network
Karush Suri, Rinki Gupta
IMUs are gaining significant importance in the field of hand gesture analysis, trajectory detection and kinematic functional study. An Inertial Measurement Unit (IMU) consists of t…
Continuous sign language recognition from wearable IMUs using deep capsule networks and game theory
Karush Suri, Rinki Gupta
Sign Language is used by the deaf community all over world. The work presented here proposes a novel one-dimensional deep capsule network (CapsNet) architecture for continuous Indi…
Activity Detection from Wearable Electromyogram Sensors using Hidden Markov Model
Rinki Gupta, Karush Suri
Surface electromyography (sEMG) has gained significant importance during recent advancements in consumer electronics for healthcare systems, gesture analysis and recognition and si…
Convolutional Neural Network Array for Sign Language Recognition using Wearable IMUs
Karush Suri, Rinki Gupta
Advancements in gesture recognition algorithms have led to a significant growth in sign language translation. By making use of efficient intelligent models, signs can be recognized…