Search Results for "dynamics"
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Showing 24 open source projects for "dynamics"
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PySINDy
A package for the sparse identification of nonlinear dynamical systems
PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. ... -
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Diffusion for World Modeling
Learning agent trained in a diffusion world model
Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within a generative model that produces frames representing the environment. This approach allows training to occur in a simulated world that captures detailed visual dynamics while reducing the need for costly interactions with real environments. ... -
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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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snntorch
Deep and online learning with spiking neural networks in Python
...This allows researchers to train spiking neural models using familiar deep learning workflows while taking advantage of GPU acceleration and automatic differentiation. snnTorch provides implementations of common spiking neuron models, surrogate gradient training methods, and utilities for handling temporal neural dynamics. Because spiking neural networks operate over time and encode information through spike timing, the library includes tools for simulating temporal behavior. -
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VectorizedMultiAgentSimulator (VMAS)
VMAS is a vectorized differentiable simulator
VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently. -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
...To reconstruct the side-chains, several tools are available. As an example, we interface with HPacker to conduct side-chain reconstruction and also provide basic tooling for running a short molecular dynamics (MD) equilibration. -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the... -
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SpikingJelly
SpikingJelly is an open-source deep learning framework
SpikingJelly is an open-source deep learning framework for spiking neural networks that is primarily built on top of PyTorch and aimed at neuromorphic computing research. The project provides the components needed to build, train, and evaluate neural models that communicate through discrete spikes rather than the continuous activations used in conventional artificial neural networks. This makes it especially relevant for researchers interested in biologically inspired computing, event-driven... -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
...It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations. -
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HN Time Capsule
Analyzing Hacker News discussions from a decade ago in hindsight
...By preserving content that might otherwise be lost to time or buried in the fast-moving flow of new posts, HN Time Capsule becomes both an educational resource and a research tool for community dynamics and tech history. -
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SleepFM-Clinical
Improve human sleep through scientifically
SleepFM-Clinical is a specialized version of SleepFM designed for clinical and research environments, offering an adaptive audio modulation system aimed at improving human sleep through scientifically guided soundscapes. Rather than simply playing static white noise or ambient tracks, it uses a closed-loop, frequency-modulated framework that responds to user-specific sleep patterns and physiological signals to tailor sound in ways that can enhance sleep onset and depth. The clinical release... -
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SlowFast
Video understanding codebase from FAIR for reproducing video models
SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without excessive computational cost. ... -
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OpenAI Swarm
Educational framework exploring multi-agent orchestration
...An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning curve. Approaches similar to Swarm are best suited for situations dealing with a large number of independent capabilities and instructions. Swarm runs (almost) entirely on the client and, much like the Chat Completions API, does not store state between calls. -
14
verl
Volcano Engine Reinforcement Learning for LLMs
...Data pipelines treat human feedback, simulated environments, and synthetic preferences as interchangeable sources, which helps with rapid experimentation. VERL is meant for both research and production hardening: logging, checkpointing, and evaluation suites are built in so you can track learning dynamics and regressions over time. -
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture, thereby enabling improved space weather forecasting. Foresees solar flares, wind, EUV spectra, and active region formation in advance. ... -
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VideoCrafter2
Overcoming Data Limitations for High-Quality Video Diffusion Models
...The system is optimized for generating videos from textual descriptions or still images, leveraging advanced diffusion models. VideoCrafter2, an upgraded version, improves on its predecessor by enhancing motion dynamics and concept combinations, especially in low-data scenarios. Users can explore a wide range of creative possibilities, producing cinematic videos that combine artistic styles and real-world scenes. -
17
Melodfy
✨:AI-Powered Piano Audio to MIDI Converter 🎶
Melodfy is an application that utilizes the power of artificial intelligence (developed by ByteDance) to seamlessly convert audio recordings of piano playing into playable MIDI files. -
18
WhisperJAV
A subtitle generator for Japanese Adult Videos.
A subtitle generator for Japanese Adult Videos. Transformer-based ASR architectures like Whisper suffer significant performance degradation when applied to the spontaneous and noisy domain of JAV. This degradation is driven by specific acoustic and temporal characteristics that defy the statistical distributions of standard training data. -
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
...Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation algorithms usually ignore the temporal dynamics and the sequence of interactions when trying to model user behavior. Generally, the next user interaction is related to the sequence of the user's previous choices. In some cases, it might be a repeated purchase or song play. User interests can also suffer from interest drift because preferences can change over time. Those challenges are addressed by the sequential recommendation task. -
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TradeMaster
TradeMaster is an open-source platform for quantitative trading
TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream... -
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MuZero General
A commented and documented implementation of MuZero
...MuZero is a model-based reinforcement learning method that combines neural networks with Monte Carlo Tree Search to learn decision-making policies without requiring explicit knowledge of the environment’s dynamics. The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train reinforcement learning agents that can learn to play games such as Atari environments or board games. The framework is modular so that users can easily add new environments by defining the game logic and associated hyperparameters. ... -
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Google Research Football
Check out the new game server
Google Research Football is a reinforcement learning environment simulating soccer matches. It focuses on learning complex behaviors such as team collaboration and strategy formation in competitive settings. -
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MuJoCo-py
mujoco-py allows using MuJoCo from Python 3
mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated. It provides utilities for loading models, running... -
24
DCVGAN
DCVGAN: Depth Conditional Video Generation, ICIP 2019.
...The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical information. To add appropriate color to the geometrical information of the scene, the domain translation from depth to color is performed for each image. ...
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