3 citations · 5 across the 7 of their papers we have counts for
7 papers
SemUV: Deep Learning based semantic manipulation over UV texture map of virtual human heads
Anirban Mukherjee, Venkat Suprabath Bitra, Vignesh Bondugula +2
Designing and manipulating virtual human heads is essential across various applications, including AR, VR, gaming, human-computer interaction and VFX. Traditional graphic-based app…
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference
Anirban Mukherjee, Hannah Hanwen Chang
Social science research often hinges on the relationship between categorical variables and outcomes. We introduce CAVIAR, a novel method for embedding categorical variables that as…
AI Knowledge and Reasoning: Emulating Expert Creativity in Scientific Research
Anirban Mukherjee, Hannah Hanwen Chang
We investigate whether modern AI can emulate expert creativity in complex scientific endeavors. We introduce novel methodology that utilizes original research articles published af…
Heuristic Reasoning in AI: Instrumental Use and Mimetic Absorption
Anirban Mukherjee, Hannah Hanwen Chang
Deviating from conventional perspectives that frame artificial intelligence (AI) systems solely as logic emulators, we propose a novel program of heuristic reasoning. We distinguis…
Psittacines of Innovation? Assessing the True Novelty of AI Creations
Anirban Mukherjee
We examine whether Artificial Intelligence (AI) systems generate truly novel ideas rather than merely regurgitating patterns learned during training. Utilizing a novel experimental…
Addressing Dynamic and Sparse Qualitative Data: A Hilbert Space Embedding of Categorical Variables
Anirban Mukherjee, Hannah H. Chang
We propose a novel framework for incorporating qualitative data into quantitative models for causal estimation. Previous methods use categorical variables derived from qualitative…