2 citations · 3 across the 16 of their papers we have counts for
5 papers · 1 filter
A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents
Abhijit Chatterjee, Niraj K. Jha, Jonathan D. Cohen +6
The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictate the prosperity and might of th…
Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need
Bhishma Dedhia, Yuval Kansal, Niraj K. Jha
Language models traditionally used for cross-domain generalization have recently demonstrated task-specific reasoning. However, their top-down training approach on general corpora…
Learning Interpretable Differentiable Logic Networks for Time-Series Classification
Chang Yue, Niraj K. Jha
Differentiable logic networks (DLNs) have shown promising results in tabular domains by combining accuracy, interpretability, and computational efficiency. In this work, we apply D…
Learning Interpretable Differentiable Logic Networks for Tabular Regression
Chang Yue, Niraj K. Jha
Neural networks (NNs) achieve outstanding performance in many domains; however, their decision processes are often opaque and their inference can be computationally expensive in re…
Generating, Fast and Slow: Scalable Parallel Video Generation with Video Interface Networks
Bhishma Dedhia, David Bourgin, Krishna Kumar Singh +5
Diffusion Transformers (DiTs) can generate short photorealistic videos, yet directly training and sampling longer videos with full attention across the video remains computationall…