Penny Liang: Understanding Large Models for Humanities Students (1.0)

"Understanding Large Models for Humanities Students (1.0)" is written by Penny Liang, offering a simplified perspective to ...

How a Paper Changed My Research Career: Dan Goodman on Reigniting the Field of Spiking Neural Networks

In the "This Paper Changed My Life" series, neuroscientists reflect on papers that have profoundly influenced their careers ...
TMCnet

WiMi Has Developed a Scalable Quantum Neural Network (SQNN) Technology Based on Multi-quantum-device Collaborative Computing

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of a Scalable Quantum Neural ...
IEEE

Quantum Neural Network Integrating with Gradient Descent Techniques for Enhanced Learning

Abstract: Quantum Machine Learning refers to the interdisciplinary area of research, blending principles from quantum physics and machine learning that can process information on quantum computers.
C&EN

GSH and Halides Directed Controllable Synthesis of Chiral Gold Nanostars for Sensitive Diagnosis of Nephritis Types Using SERS and Transformer Neural Network

Institute of Digitized Medicine and Intelligent Technology, Wenzhou Medical University, Wenzhou 325000, P. R. China ...
GitHub

NeuralBot - Neural Network Aimbot

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...
Phys.org

DNA-based neural network learns from examples to solve problems

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...
IEEE

Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks

Abstract: Stochastic gradient descent (SGD) is widely believed to perform implicit regularization when used to train deep neural networks, but the precise manner in which this occurs has thus far been ...
GitHub

Vision-Language Gradient Descent-driven All-in-One Deep Unfolding Networks

Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...
C&EN

Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine Learning Force Fields (MLFFs) promise to enable general molecular simulations ...