ivanalberico / Probabilistic-Artificial-Intelligence-ETHLinks
Graded projects of the course "Probabilistic Artificial Intelligence", ETH Zürich (Fall 2020). Topics: Gaussian Process Regression, Bayesian Neural Networks, Bayesian Optimization, Deep Reinforcement Learning.
☆11Updated 4 years ago
Alternatives and similar repositories for Probabilistic-Artificial-Intelligence-ETH
Users that are interested in Probabilistic-Artificial-Intelligence-ETH are comparing it to the libraries listed below
Sorting:
- 高斯过程回归☆85Updated 3 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆43Updated 6 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆99Updated 4 years ago
- multivariate Gaussian process regression and multivariate Student-t process regression☆77Updated last month
- Prediction of continuous signals data and Web tracking data using dynamic Bayesian neural network. Compared with other network architectu…☆42Updated 7 years ago
- ☆16Updated 4 years ago
- Pyro/Pytorch implementation of Deep Kalman FIlter for shared-mobility demand prediction☆48Updated 6 years ago
- Pytorch Implementation of Deep Kalman Filter☆11Updated 3 months ago
- Neural Extended Kalman Filters☆18Updated 2 years ago
- This repository contains PyTorch implementations of Neural Process, Attentive Neural Process, and Recurrent Attentive Neural Process.☆19Updated 5 years ago
- Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the tempora…☆39Updated 7 years ago
- ☆36Updated 7 years ago
- Gaussian Process Model Dynamic System Identification Toolbox for Matlab☆94Updated 8 years ago
- Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"☆39Updated last year
- [Applied Energy] This work proposes an Input Convex LSTM neural network for real-time neural network-based optimization.☆18Updated 8 months ago
- State-space deep Gaussian processes in Python and Matlab☆30Updated 3 years ago
- Gaussian Process Regression Techniques - The source code corresponding to the Ph.D. thesis.☆72Updated 8 years ago
- Mixtures of Gaussian Process Experts in GPflow/TensorFlow☆12Updated 3 years ago
- Extended Kalman filter for training neural-networks☆97Updated 5 years ago
- Incorporating Transformer and LSTM to Kalman Filter with EM algorithm☆200Updated 3 years ago
- Bayesian System IDentification☆27Updated 7 years ago
- ☆24Updated 3 years ago
- Deep learning based state estimation: incorporating Transformer and LSTM to Kalman Filter with EM algorithm.☆12Updated last week
- Multimodal Supervised Variational Autoencoder☆18Updated 5 years ago
- Toy models, experiments and random notes on machine learning and deep learning.☆129Updated last year
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆50Updated 5 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆33Updated 3 years ago
- PyTorch Implementation of Lusch et al DeepKoopman☆15Updated 3 years ago
- ☆16Updated 7 years ago
- The project uses a nonlinear autoregressive exogenous (NARX), model to make time-series prediction on data obtained from drive cycling te…☆39Updated 2 years ago