26 citations · 181 across the 49 of their papers we have counts for
11 papers · 1 filter
HALSIE: Hybrid Approach to Learning Segmentation by Simultaneously Exploiting Image and Event Modalities
Shristi Das Biswas, Adarsh Kosta, Chamika Liyanagedera +2
Event cameras detect changes in per-pixel intensity to generate asynchronous `event streams'. They offer great potential for accurate semantic map retrieval in real-time autonomous…
KSAT: Knowledge-infused Self Attention Transformer -- Integrating Multiple Domain-Specific Contexts
Kaushik Roy, Yuxin Zi, Vignesh Narayanan +2
Domain-specific language understanding requires integrating multiple pieces of relevant contextual information. For example, we see both suicide and depression-related behavior (mu…
Synthetic Dataset Generation for Privacy-Preserving Machine Learning
Efstathia Soufleri, Gobinda Saha, Kaushik Roy
Machine Learning (ML) has achieved enormous success in solving a variety of problems in computer vision, speech recognition, object detection, to name a few. The principal reason f…
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions
Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy
Decentralized learning over distributed datasets can have significantly different data distributions across the agents. The current state-of-the-art decentralized algorithms mostly…
Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics
Adarsh Kumar Kosta, Kaushik Roy
Event-based cameras have recently shown great potential for high-speed motion estimation owing to their ability to capture temporally rich information asynchronously. Spiking Neura…
Can Language Models Capture Graph Semantics? From Graphs to Language Model and Vice-Versa
Tarun Garg, Kaushik Roy, Amit Sheth
Knowledge Graphs are a great resource to capture semantic knowledge in terms of entities and relationships between the entities. However, current deep learning models takes as inpu…
Process Knowledge-Infused AI: Towards User-level Explainability, Interpretability, and Safety
Amit Sheth, Manas Gaur, Kaushik Roy +2
AI systems have been widely adopted across various domains in the real world. However, in high-value, sensitive, or safety-critical applications such as self-management for persona…
Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts
Shrey Gupta, Anmol Agarwal, Manas Gaur +4
Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide in…
Norm-Scaling for Out-of-Distribution Detection
Deepak Ravikumar, Kaushik Roy
Out-of-Distribution (OoD) inputs are examples that do not belong to the true underlying distribution of the dataset. Research has shown that deep neural nets make confident mispred…
Process Knowledge-infused Learning for Suicidality Assessment on Social Media
Kaushik Roy, Manas Gaur, Qi Zhang +1
Improving the performance and natural language explanations of deep learning algorithms is a priority for adoption by humans in the real world. In several domains, such as healthca…
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
Isha Garg, Manish Nagaraj, Kaushik Roy
Advances in Federated Learning and an abundance of user data have enabled rich collaborative learning between multiple clients, without sharing user data. This is done via a centra…