GitHub

TurboQuant PyTorch — Implementation + Deep Tutorial

A from-scratch PyTorch implementation of TurboQuant (ICLR 2026), Google's two-stage vector quantization algorithm for compressing LLM key-value caches — enhanced with a comprehensive, research-grade ...
IEEE

Mid-Term Load Forecasting With Minimal Data: An In-Context-Learning-Aware Approach Using Large Language Models

Abstract: Accurate mid-term load forecasting at the building level is vital for the strategic planning, operation, and sustainability of modern power systems. Machine learning approaches often require ...
IEEE

Advanced Preprocessing Techniques for Transaction Data Analysis

Abstract: The analysis of transaction data is often impeded by challenges such as noise, inconsistencies, high dimensionality, and missing values, which obscure valuable insights. Existing ...
GitHub

OHBA-analysis/MEG-Mamba

Inputs tokens (N, L) channel_ids (N,) session_ids (N,) N channel-sequences — one parcel's token stream each Embed → (N, L, d_model) token_emb[tokens] token lookup + channel_emb[channel_ids] per-parcel ...
Frontiers

The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives

Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain ...