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t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark
3D adaptive binary space partitioning and beyond
A list of recent papers about adversarial learning
This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
SLO- and input-aware resource configuration optimization for serverless workflows
Official code for the ICML 2024 paper "The Entropy Enigma: Success and Failure of Entropy Minimization"
Simple and easily configurable grid world environments for reinforcement learning
Implements the Karnin-Lang-Liberty (KLL) algorithm in python
A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
Implementation of BTree part for paper 'The Case for Learned Index Structures'
The recursive model index, a learned index structure
Error-bounded Lossy Data Compressor (for floating-point/integer datasets)
A prototype for paper "Enabling Efficient and General Subpopulation Analytics In Multidimensional Data Streams" to appear at VLDB 2022
Bubble Sketch: A High-performance and Memory-efficient Sketch for Finding Top-k Items in Data Streams (ACM CIKM 2024)
Scalable and user friendly neural 🧠 forecasting algorithms.
Lightning ⚡️ fast forecasting with statistical and econometric models.
Python implementations of the distributed quantile sketch algorithm DDSketch
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
Code for the paper "Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents"
A playbook for systematically maximizing the performance of deep learning models.
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.