vishalbelsare,Vishal Belsare,github

affective_preference_rhythm

Data release for Global Music Streaming Data Reveals Diurnal and Seasonal Patterns of Affective Preference

affineflowcausalinf

Code for "Autoregressive flow-based causal discovery and inference" - ICML INNF workshop, 2020

affinewarp

An implementation of piecewise linear time warping for multi-dimensional time series alignment

aftershocks_issues

Issues with Deep Learning of Aftershocks by DeVries

agensgraph

AgensGraph, a transactional graph database based on PostgreSQL

agensgraph-extension

A graph database extension for PostgreSQL

agentmodels.org

Modeling agents with probabilistic programs

agentpy

AgentPy is an open-source framework for the development and analysis of agent-based models in Python.

agents-aea

A framework for autonomous economic agent (AEA) development

aggforecaster

Code for "Long Range Probabilistic Forecasting in Time-Series using High Order Statistics"

agora

A sandbox for building and testing scalable implementations of various market micro-structures.

ags_nlp_solver

Derivative-free nonlinear global optimizer with python interface

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

ai-for-time-series-papers-tutorials-surveys

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

ai-ml-ripperk

A high performance rule induction algorithm (RIPPERk).

ai-privacy-toolkit

A toolkit for tools and techniques related to the privacy and compliance of AI models.

ai-python

A collection of Python Packages for AI usecases

ai_stock_trading

Design pattern for critical stages in the development process of an AI Stock Trading Bot

aictr

Zhao-Rong Lai, Dao-Qing Dai, Chuan-Xian Ren, and Ke-Kun Huang, “Radial basis functions with adaptive input and composite trend representation for portfolio selection”, IEEE Transactions on Neural Networks and Learning Systems, 2018.