GitHub

Cell Decoder: Decoding cell identity with multi-scale explainable deep learning

We created the python package called celldecoder that that decoding cell identity from gene expressions by explicitly modeling the multi-scale biological interactions, i.e., genes, pathways, and ...
marktechpost

Google DeepMind Introduces Unified Latents (UL): A Machine Learning Framework that Jointly Regularizes Latents Using a Diffusion Prior and Decoder

Generative AI’s current trajectory relies heavily on Latent Diffusion Models (LDMs) to manage the computational cost of high-resolution synthesis. By compressing data into a lower-dimensional latent ...
TV Technology

Miri to Showcase New V410 Video Encoder/Decoder at ISE 2026

READING, Pa.—Miri Technologies has unveiled the V410 live 4K video encoder/decoder for streaming, IP-based production workflows and AV-over-IP distribution, which will make its world debut at ISE 2026 ...
IEEE

Encoder-Decoder Based Deep Reinforcement Learning for Multi-AUV Assisted Data Collection in UWSNs

Abstract: Reliable and timely data collection poses a significant challenge for underwater wireless sensor networks (UWSNs), primarily due to the extremely low data rate of underwater communication ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
GitHub

Deep Reinforcement Learning for Service Function Chain Placement with Graph Attention and Transformer Encoder

This repository contains the implementation of the paper of paper Deep Reinforcement Learning for Service Function Chain Placement with Graph Attention and Transformer Encoder. In this paper, we ...
Frontiers

A combined approach to lithology identification using reinforcement learning and transformer algorithms

Lithology identification plays a pivotal role in logging interpretation during drilling operations, directly influencing drilling decisions and efficiency. Conventional lithology identification ...
marktechpost

This AI Paper Proposes a Novel Dual-Branch Encoder-Decoder Architecture for Unsupervised Speech Enhancement (SE)

Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...