GitHub

This repo describes python code and input data files for "Forecasting stock return distributions around the globe with quantile neural networks".

torch 2.2.2 PyTorch framework for neural networks. The documented GPU setup targets the official CUDA 12.1 wheel. FF3.CSV Ken French Data Library Full file included Fama-French 3-factor returns. Only ...

Meta launches image generation model with coding, search capabilities

Meta Platforms Inc. today debuted an image generation model that can write code and search the web. Muse Image is the second ...
Frontiers

Next-gen neuro-AI: Aligning foundation models and biologically plausible architectures with human cognition

Cognitive computational neuroscience has entered a transformative era. The rapid rise of large multimodal foundation models, state-space architectures, and ...
How-To Geek on MSN

These 7 Python libraries are useful even if you're not a developer

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.
IEEE

CARLA-GeAR: A Dataset Generator for a Systematic Evaluation of Adversarial Robustness of Deep Learning Vision Models

Abstract: Adversarial examples represent a serious threat for deep neural networks in several application domains and a huge amount of work has been produced to investigate them and mitigate their ...
GitHub

GitHub - facebookincubator/AITemplate: AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore ...

High performance: close to roofline fp16 TensorCore (NVIDIA GPU) / MatrixCore (AMD GPU) performance on major models, including ResNet, MaskRCNN, BERT, VisionTransformer, Stable Diffusion, etc. Unified ...