Scientific Research Publishing

Machine Learning for Financial Risk Management: Modeling Time-Varying Factor Sensitivities Using Factor Variational Autoencoders ()

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
IEEE

Blind Polarisation Demultiplexing and Carrier Recovery Using FIR-based Variational AutoEncoder Equaliser for Probabilistic Constellation Shaping in Optical Fibre Communications

Abstract: We investigate through simulations the potential of Finite Impulse Response (FIR)-based Variational AutoEncoder-inspired (VAE-FIR) equaliser for polarisation demultiplexing, Carrier Phase ...
GitHub

Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders

Note: We have recently found that Dora-VAE can specify tokens of any length during inference, even if this length has not been seen during training. During inference, you could use a latent code ...
TheServerSide

How to use Claude Desktop tutorial for beginners

Founded by former OpenAI staff members and funded by Amazon and Google, Anthropic has raised the stakes in the GPT wars. Anthropic's Claude Desktop app often outshines its ChatGPT rival in various ...
GitHub

dk-a-dev/anomaly-detection-iot-data

A comprehensive Python-based machine learning solution for detecting anomalies in multivariate time series data from industrial IoT sensors. This solution identifies abnormal behavior patterns and ...
IEEE

Numerical Investigation of Bending Tolerance of Multimode Optical Fiber Imaging with Variational Autoencoder

Abstract: We propose a Variational Autoencoder-based image reconstruction through a multimode optical fiber. Simulations under bending conditions achieved 96% accuracy, demonstrating the feasibility ...