Zobrazeno 1 - 10
of 862
pro vyhledávání: '"Mukherjee, Anirban"'
We characterize steady-state static and dynamic properties in a broad class of mass transport processes on a periodic hypercubic lattice of volume $L^d$, where both mass and {\it center-of-mass} (CoM) remain conserved and detailed balance is violated
Externí odkaz:
http://arxiv.org/abs/2410.00613
Autor:
Mukherjee, Anirban, Bitra, Venkat Suprabath, Bondugula, Vignesh, Tallapureddy, Tarun Reddy, Jayagopi, Dinesh Babu
Designing and manipulating virtual human heads is essential across various applications, including AR, VR, gaming, human-computer interaction and VFX. Traditional graphic-based approaches require manual effort and resources to achieve accurate repres
Externí odkaz:
http://arxiv.org/abs/2407.00229
Autor:
Cañellas, Manuel Lage, Nguyen, Le, Mukherjee, Anirban, Casado, Constantino Álvarez, Wu, Xiaoting, Susarla, Praneeth, Sharifipour, Sasan, Jayagopi, Dinesh B., López, Miguel Bordallo
In the domain of non-contact biometrics and human activity recognition, the lack of a versatile, multimodal dataset poses a significant bottleneck. To address this, we introduce the Oulu Multi Sensing (OMuSense-23) dataset that includes biosignals ob
Externí odkaz:
http://arxiv.org/abs/2407.06137
Social science research often hinges on the relationship between categorical variables and outcomes. We introduce CAVIAR, a novel method for embedding categorical variables that assume values in a high-dimensional ambient space but are sampled from a
Externí odkaz:
http://arxiv.org/abs/2404.04979
We investigate whether modern AI can emulate expert creativity in complex scientific endeavors. We introduce novel methodology that utilizes original research articles published after the AI's training cutoff, ensuring no prior exposure, mitigating c
Externí odkaz:
http://arxiv.org/abs/2404.04436
Autor:
Mukherjee, Anirban
We examine whether Artificial Intelligence (AI) systems generate truly novel ideas rather than merely regurgitating patterns learned during training. Utilizing a novel experimental design, we task an AI with generating project titles for hypothetical
Externí odkaz:
http://arxiv.org/abs/2404.00017
Autor:
Mukherjee, Anirban
Generative AI has ushered in the ability to generate content that closely mimics human contributions, introducing an unprecedented threat: Deployed en masse, these models can be used to manipulate public opinion and distort perceptions, resulting in
Externí odkaz:
http://arxiv.org/abs/2403.14706
Face de-identification in videos is a challenging task in the domain of computer vision, primarily used in privacy-preserving applications. Despite the considerable progress achieved through generative vision models, there remain multiple challenges
Externí odkaz:
http://arxiv.org/abs/2403.10058
Deviating from conventional perspectives that frame artificial intelligence (AI) systems solely as logic emulators, we propose a novel program of heuristic reasoning. We distinguish between the 'instrumental' use of heuristics to match resources with
Externí odkaz:
http://arxiv.org/abs/2403.09404
Theory of Mind (ToM) refers to the ability to attribute mental states, such as beliefs, desires, intentions, and knowledge, to oneself and others, and to understand that these mental states can differ from one's own and from reality. We investigate T
Externí odkaz:
http://arxiv.org/abs/2403.09289