This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Abstract: Implicit neural representations (INRs) such as NeRF and SIREN encode a signal in neural network parameters and show excellent results for signal reconstruction. Using INRs for downstream ...

Fulfilment services startup QuickShift has raised INR 22 Cr ($2.5 Mn) in a Pre-Series A round led by Atomic Capital, with participation from Axilor Ventures and a few other unnamed investors. The ...

Abstract: Optimizing the performance of deep neural networks (DNNs) remains a significant challenge due to the sensitivity of models to both hyperparameter selection and weight initialization.

In cellular automata, simple rules create elaborate structures. Now researchers can start with the structures and reverse-engineer the rules. Alexander Mordvintsev showed me two clumps of pixels on ...

E2E Networks has received a contract letter from IndiaAI Mission to provide GPU resources worth INR 177 Cr to Gnani.ai E2E Networks will be allocating H100 SXM and H200 SXM GPU resources to the ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

What is CNN in Deep Learning? In this video, we understand what is CNN in Deep Learning and why do we need it. CNN (or Convolutional Neural Network) is the building block of all Computer Vision ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...

physics_informed_neural_network/ ├── app/ # FastAPI application │ ├── __init__.py │ ├── api/ # API endpoints │ │ ├── __init__.py ...