Neural network weight quantification
In the era of increasingly large language models and complex neural networks, optimizing model efficiency has become paramount. Weight quantization ...
Tag: neural
Neural Networks for Time Series Imputation: Addressing Missing Data | by Sara Nóbrega | January 2025
Part 3: Discover how a simple Keras sequential model can be effectiveSource: DALL-E.One of the common problems in Time series ...
Google AI introduces ZeroBAS: a neural method for synthesizing binaural audio from monaural audio recordings and positional information without training with binaural data
Humans have an extraordinary ability to locate sound sources and interpret their environment using auditory signals, a phenomenon called spatial ...
CMU researchers introduce TNNGen: an AI framework that automates the design of temporal neural networks (TNNs) from PyTorch software models to post-design netlists
The design of neuromorphic sensory processing units (NSPUs) based on temporal neural networks (TNNs) is a very challenging task due ...
Superposition: what makes it difficult to explain neural networks | by Shuyang Xiang | December 2024
When there are more features than dimensions of the modelIt would be ideal if the world of neural networks represented ...
NeuralOperator – A new Python library for learning neural operators in PyTorch
Operator learning is a transformative approach in scientific computing. It focuses on the development of models that map functions to ...
Hypergrid Fields: Efficient Gradient-Based Training for Scalable Neural Network Optimization
Hypernetworks have attracted attention for their ability to efficiently adapt large models or train generative models of neural representations. Despite ...
Neural Networks for Scalable Temporal Logic Model Verification in Hardware Verification
Ensuring the accuracy of electronic designs is essential, as hardware failures are permanent in post-production and can compromise the reliability ...
Tencent Research Introduces DRT-o1: Two Variants DRT-o1-7B and DRT-o1-14B With a Breakthrough in Neural Machine Translation for Literary Texts
Neural machine translation (NMT) is a sophisticated branch of natural language processing that automates the conversion of text between languages ...
Eleuther AI introduces new machine learning framework to analyze neural network training via Jacobian matrix
Neural networks have become fundamental tools in computer vision, NLP, and many other fields, offering capabilities to model and predict ...
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