Nitish is a computer science undergraduate with keen interest in the field of deep learning. He has done various projects related to deep learning and closely follows the new advancements taking place in the field.
Long-form question-answering (LFQA), a paragraph-length answer created in response to an open-ended question, is a growing difficulty in NLP. LFQA systems hold the potential...
In games and robotics simulators, reinforcement learning has demonstrated competitive performance. Solving mathematical optimization issues with RL approaches has recently attracted a lot of...
The discovery, design, and testing phases of the drug development process are iterative. Drugs were previously sourced from plants and found through trial-and-error methods....
Tight rules generally govern data sharing in highly regulated industries like finance and healthcare. Federated learning is a distributed learning system that allows multi-institutional...
Scientists look for drug-like compounds that can connect to disease-causing proteins and modify their functionality to search for new therapies. They must grasp a...
By developing fresh images, generative image models provide a distinct value. These photos could be clear super-resolution copies of current images or even manufactured...
Model inversion (MI), where an adversary abuses access to a trained Machine Learning (ML) model in order to infer sensitive information about the model's...
'The Mixture of Experts (MoE) architecture is a deep learning model architecture in which the computational cost is proportional to the number of parameters,...
The ventral visual stream is widely known for supporting the perception of faces and objects. Extracellular single neuron recordings define canonical coding principles at...
The ImageNet database, which was first introduced at the Conference of Computer Vision and Pattern Recognition in 2009 and today contains over 14 million...
Natural language generation (NLG) is a broad term that encompasses a variety of tasks that generate fluent text from input data and other contextual...
