A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
UniFeat is an open-source Java tool for feature selection.
Fine-tuned open-source LLMs match or exceed closed-source models in social science research.
Study uses open data to improve traffic emissions estimation.
FinGPT is an open-source financial LLM for democratizing financial data.
This paper presents an open-source enforcement learning toolkit named CytonRL (https://github.com/arthurxlw/cytonRL). The toolkit implements four recent advanced deep Q-learning algorithms from scratch using C++ and NVIDIA's GPU-accelerated libraries. The code is simple and elegant, owing to an open-source general-purp…
This paper benchmarks FinGPT for financial datasets using open-source large language models.
We provide complete source code for building a fundamental industry classification based on publically available and freely downloadable data. We compare various fundamental industry classifications by running a horserace of short-horizon trading signals (alphas) utilizing open source heterotic risk models (https://ssr…
Integrates multiple datasets to solve open set crowdsourcing problems.
FinRobot opens-source AI for financial tasks, breaking down complex problems.
End-to-end PGL framework tackles open-set domain shift.
In recent years, an active field of research has developed around automated machine learning (AutoML). Unfortunately, comparing different AutoML systems is hard and often done incorrectly. We introduce an open, ongoing, and extensible benchmark framework which follows best practices and avoids common mistakes. The fram…
Apache Spark is a popular open-source platform for large-scale data processing that is well-suited for iterative machine learning tasks. In this paper we present MLlib, Spark's open-source distributed machine learning library. MLlib provides efficient functionality for a wide range of learning settings and includes sev…
This paper argues for decolonizing AI alignment by incorporating open-source Hinduism concepts.
AutoML serves as the bridge between varying levels of expertise when designing machine learning systems and expedites the data science process. A wide range of techniques is taken to address this, however there does not exist an objective comparison of these techniques. We present a benchmark of current open source Aut…
This study examines representation bias in open-source Qwen models for investment decisions.
Paper tackles open set domain adaptation by detecting unknown classes.
SAGDA generates synthetic agricultural datasets to improve ML in African farming.
The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model's learning performance with an unlabeled (target) domain -- the basic strategy being to mitigate the effects of discrepancies between the two distributions. Most existing algorithms can only handle uns…
Deep learning methods have shown extraordinary potential for analyzing very diverse biomedical data, but their dissemination beyond developers is hindered by important computational hurdles. We introduce ImJoy (https://imjoy.io/), a flexible and open-source browser-based platform designed to facilitate widespread reuse…
Recently, a lot of papers proposed to use neural networks to approximately solve partial differential equations (PDEs). Yet, there has been a lack of flexible framework for convenient experimentation. In an attempt to fill the gap, we introduce a PyDEns-module open-sourced on GitHub. Coupled with capabilities of BatchF…
This paper presents the philosophy, design and feature-set of Neural Network Distiller, an open-source Python package for DNN compression research. Distiller is a library of DNN compression algorithms implementations, with tools, tutorials and sample applications for various learning tasks. Its target users are both en…
Scoping review and benchmarking of synthetic EHR data generation methods.
Optimal transport method rejects new classes and adjusts class ratios for open set domain adaptation.
HuSpaCy offers an industrial-grade Hungarian NLP toolkit.
BoFire optimizes chemistry experiments using Bayesian Optimization.
Uncertainty Toolbox aids in assessing and improving uncertainty quantification in machine learning.
FinGPT democratizes financial data for LLMs, enabling innovation.
Increasing numbers of software vulnerabilities are discovered every year whether they are reported publicly or discovered internally in proprietary code. These vulnerabilities can pose serious risk of exploit and result in system compromise, information leaks, or denial of service. We leveraged the wealth of C and C++ …
EmTract extracts emotions from financial social media text.
SurvSet offers a repository of 76 T2E datasets for ML benchmarking.
This paper is concerned with structured machine learning, in a supervised machine learning context. It discusses how to make joint structured learning on interdependent objects of different nature, as well as how to enforce logical con-straints when predicting labels. We explain how this need arose in a Document Unders…
CoinTossX is a low-latency, open-source matching engine for financial trading.
Due to the threat of climate change, a transition from a fossil-fuel based system to one based on zero-carbon is required. However, this is not as simple as instantaneously closing down all fossil fuel energy generation and replacing them with renewable sources -- careful decisions need to be taken to ensure rapid but …
We provide an online RLHF workflow for large language models.
A new method trains deep neural networks for open set domain adaptation without negative open set difference.
ICLR 2021 challenge in computational geometry and topology attracted 16 teams.
The scientific literature is a rich source of information for data mining with conceptual knowledge graphs; the open science movement has enriched this literature with complementary source code that implements scientific models. To exploit this new resource, we construct a knowledge graph using unsupervised learning me…
AHN package simplifies supervised learning with hydrocarbon networks.
SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks. SMART provides users with an intuitive interface for creating labeled data sets, supports active learning to help reduce the required amount of …
3D CNNs interpret brain MRI differences between men and women.
Deep Learning has established itself to be a common occurrence in the business lexicon. The unprecedented success of deep learning in recent years can be attributed to: abundance of data, availability of gargantuan compute capabilities offered by GPUs, and adoption of open-source philosophy by the researchers and indus…
New framework tackles multi-source domain adaptation with optimism and consistency.
OtoWorld helps agents learn to navigate by listening in interactive environments.
Cyanure is an open-source C++ software package with a Python interface. The goal of Cyanure is to provide state-of-the-art solvers for learning linear models, based on stochastic variance-reduced stochastic optimization with acceleration mechanisms. Cyanure can handle a large variety of loss functions (logistic, square…
The AlphaGo, AlphaGo Zero, and AlphaZero series of algorithms are remarkable demonstrations of deep reinforcement learning's capabilities, achieving superhuman performance in the complex game of Go with progressively increasing autonomy. However, many obstacles remain in the understanding of and usability of these prom…
LeanDojo removes barriers to theorem proving with open-source tools and data.
Study benchmarks embedding-based entity alignment methods for KGs.
NoLimits.jl: Flexible and Composable Nonlinear Mixed-Effects Modeling in Julia