Tom's Hardware on MSN

Nvidia details Rubin architectural optimizations for inference

Nvidia has detailed new features of its Rubin architecture.
IEEE

NormMax: A Robust L2-Normalization Activation Function with Precision-Scalable Hardware Architectures for Noisy-Label Learning

Abstract: Label noise in real-world datasets poses a significant challenge for deep neural networks, particularly in image classification tasks, where it disrupts learning and degrades performance.
XDA Developers on MSN

I tested every tiny local LLM worth running, and only three survived the cut

Small models are doing more than they should ...
IEEE

SQIX: QMIX Algorithm Activated by General Softmax Operator for Cooperative Multiagent Reinforcement Learning

Abstract: Multiagent cooperative systems can be used to conceptualize many real-world problems. Reinforcement learning is a particularly effective tool. The issue of bias in Q-function value ...
GitHub

Time2Vec: Learning a Vector representation of Time

This is an attempt of reproducing the paper "Time2Vec: Learning a Vector Representation of Time" in PyTorch. For Pretrained model and package to encode ISO Date-Time to vectors, please check Date2Vec ...
GitHub

Verilog implementation of Softmax function

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...