Search Results for "q-chem" - Page 2
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Showing 62 open source projects for "q-chem"
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PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
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AS Arrow
Add and Subtract game
...In the similar way, the next card is positive (add/plus), and then the card is negative (subtract/minus). The row of cards can be deleted as sum (add/subtract) of cards is 0. (J is 11,Q is 12, K is 13) If the number of cards is 12, but can't be deleted now. The game is over. By the way, if cards library is empty and user can't win, the game is over. v0.1.1 Update: You can move an entire pile to another pile (except the first card). If the front half of a pile becomes 0 after applying + / −, you must click the next card pile (the card immediately after that 0) to auto-remove -
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TobbeOS
TobbeOS is a GNU/Linux distro based on Arch linux
...Important keys to know about: Mod = Super key (Windows key) Mod + E - Open Emacs - Need to install with script tobbeos/emacs_install.sh Mod + Return - Open Terminal (Kitty) Mod + s - Show hotkeys Mod + left Shift + s - Show alias for fish shell Mod + left Shift + Tab - Open web browser (Zen) Mod + left Shift + q - kill window Mod + d - Rofi (Program Launcher) !!!!! ISO is moved, go to: https://tobbeos.lysakermoen.com/ and install latest ISO !!!!! -
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GLM-4-32B-0414
Open Multilingual Multimodal Chat LMs
GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced... -
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minimalRL-pytorch
Implementations of basic RL algorithms with minimal lines of codes
...Each algorithm implementation is contained within a single file and typically ranges from about 100 to 150 lines of code, making it easy for learners to inspect the entire implementation at once. The repository includes examples of widely used reinforcement learning methods such as REINFORCE, Deep Q-Networks, Proximal Policy Optimization, and Actor-Critic architectures. Most experiments are designed to run quickly using the CartPole environment so that users can focus on understanding algorithm logic rather than computational infrastructure. -
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GXSM
Scanning Probe Microscopy Controller and Data Visualization Software
GXSM -- Gnome X Scanning Microscopy: A multi-channel image and vector-probe data acquisition and visualization system designed for SPM techniques (STM,AFM..), but also SPA-LEED/LEED/LEEM data analysis. A plug-in interface allows any user add-on data-processing and special hardware and instrument support. Latest: NC-AFM and related explorative methods as SQDM can be configured. High-Speed external PAC-PLL hardware option with digital DSP link. Based on several hardware options it supports... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. ... -
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Reinforcement Learning Methods
Simple Reinforcement learning tutorials
Reinforcement-Learning-with-TensorFlow is an educational repository that walks through key reinforcement learning algorithms implemented in TensorFlow. It provides clear code examples for foundational techniques like Q-learning, policy gradients, deep Q-networks, actor-critic methods, and value function approximation within familiar simulation environments. Each algorithm is structured with readable code, explanatory comments, and corresponding environment interaction loops so learners can easily trace how actions, rewards, and model updates connect. ... -
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TheoDORE
Theoretical Density, Orbital Relaxation and Exciton analysis
...Wavefunction analysis is based on state and transition density matrices, which provides a unified formalism applicable independent of the wavefunction model. TheoDORE is interfaced to a number of quantum chemical programs (Q-Chem, Columbus, Turbomole, ...) and can be used for a wide range of excited state methods (MR-CI, ADC, CC, TDDFT). It is written in a modular fashion to allow for an easy extension of these capabilities. Code development moved to github: https://github.com/felixplasser/theodore-qc -
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q - Text as Data
Run SQL directly on CSV or TSV files
q is a command line tool that allows direct execution of SQL-like queries on CSVs/TSVs (and any other tabular text files). q treats ordinary files as database tables, and supports all SQL constructs, such as WHERE, GROUP BY, JOINs etc. It supports automatic column name and column type detection, and provides full support for multiple encodings. q fully supports all types of encoding. -
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TRFL
TensorFlow Reinforcement Learning
...TRFL supports both CPU and GPU TensorFlow environments, though TensorFlow itself must be installed separately. It exposes clean, modular APIs for various RL methods including Q-learning, policy gradient, and actor-critic algorithms, among others. Each function returns not only the computed loss tensor but also a detailed structure containing auxiliary information like TD errors and targets. -
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onnxt5
Summarization, translation, sentiment-analysis, text-generation, etc.
Summarization, translation, sentiment analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in the alpha stage, therefore some functionalities such as beam searches are still in development. The simplest way to get started for generation is to use the default pre-trained version of T5 on ONNX included in the package. Please note that the first time you call get_encoder_decoder_tokenizer, the models are being downloaded which might... -
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PaddlePaddle models
Pre-trained and Reproduced Deep Learning Models
Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,... -
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. -
15
2D Structural Analysis
Determine the bending moments, shear forces, axial forces and displace
2D Structural Analysis in Python by Ritchie Vink A collection examples of 2D Finite Element Analysis (FEA) made with Jupyter Notebook Lab - https://jupyter.org/ To install Jupyter - https://jupyter.org/install ===== App is available on Play Store -> https://play.google.com/store/apps/details?id=com.ulm.struct If you want to download a python editor for your android smartphone follow this link -> https://play.google.com/store/apps/details?id=com.ulm.python -
16
qqbot
A conversation robot base on Tencent's SmartQQ
...You need to scan the code with the mobile QQ client and authorize the login. After the startup is successful, the current login information will be saved to the local file. When the next startup, you can enter: qqbot -q qq number , first try to restore the login information from the local file (no need to scan the code manually), only if the recovery fails Only when the login information is successful or the login information has expired will you need to scan the QR code to log in manually. Generally, saved login information will expire after 2 days. ... -
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Teach Me Quantum
Practical Course on Quantum Information Science and Quantum Computing
A university-level course on Quantum Computing and Quantum Information Science that incorporates IBM Q Experience and Qiskit. This course is adequate for general audiences without prior knowledge on Quantum Mechanics and Quantum Computing (see prior knowledge), has an estimated average duration of 10 weeks at 3h/week (see duration), and is meant to be the entrypoint into the Quantum World. -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda... -
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Deep Reinforcement Learning TensorFlow
TensorFlow implementation of Deep Reinforcement Learning papers
...The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural networks can be trained through interaction with simulated environments. The project is commonly used by learners who want to move beyond theory and understand the practical mechanics of training RL agents. Visualization utilities and training scripts help users monitor learning progress and debug experiments. -
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Deep Reinforcement Learning for Keras
Deep Reinforcement Learning for Keras.
keras-rl implements some state-of-the-art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course, you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and... -
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WidgetArea
WidgetArea is a small simple application that enables you to use image
...Mac Usage Instructions: Click the upload image or drag and drop an image there to display in a new window. To close the newly opened image press "CMD+W". To quit WidgetArea press "CMD+Q" To move the image just drag it anywhere on the screen. Yes, you can resize added images in this release. There's no built-in option to adjust pinning or transparency in this release. However, WidgetArea for Mac does support transparent PNG's and GIF images. -
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orbkit (Moved to Github)
A Modular Python Toolbox for Cross-Platform Post-Processing of Quantum
...If you use orbkit in your work, please cite it as follows: Gunter Hermann, Vincent Pohl, Jean Christophe Tremblay, Beate Paulus, Hans-Christian Hege, and Axel Schild, "ORBKIT: A Modular Python Toolbox for Cross-Platform Postprocessing of Quantum Chemical Wavefunction Data", J. Comput. Chem. 2016, DOI: 10.1002/jcc.24358. orbkit's documentation can be found at http://orbkit.github.io/ -
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AutoSigRecog
Automatic Signal Recognition
A tool to analyze I/Q recording saved as standard WAV file to find signal and their type (AM/FM/PM/SSB.... and so on). At moment under deep development... be patient, I'm not a pro developer! -
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2048 Python , AI , 1 or 2 players
py 2048, a well know 2048 clone board game
...-add HiScore for Small, Medium And Large Panel Game -check for close windows as QUIT event. -add Change theme screen BckGnd on score tile. -add counter move V0.1.2: -compliant Pyhton34 -add AI Auto Boot -add 2 players Human/AI (keys A,Q,W,X) -
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2DMED
Phase Sensitive Detection and Modulated Enhanced Diffraction Software
2DMED it is the second out of two programs which allows implementation of Phase Sensitive Detection (PSD) and/or Modulated Enhanced Diffraction (MED) techniques on the in situ data. This software takes normalized and averaged in situ data in flat file format (FLT) and performs PSD transformation which has been described in Urakawa, A.et al. Chem. Eng. Science 2008, 63, 4902. User can choose demodulation index k and perform several demodulation calculations. This is extremely important since demodulation calculations at k = 2 on in situ powder diffraction data represent implementation of MED method which been described in Chernyshov, D. et al. Acta Cryst. 2011, A67, 327. Demodulated data can be then viewed on 2D and/or 1D plot and analyses with different tools including In Phase Plot, Maximum Amplitude Plot and Positive Pattern Plot. ...
