"Your Fully-Automated Personal AI Assistant"

A simple agent framework that's capable of browser use + mcp + auto instrument + plan + deep research + more

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

Recently, realistic image generation using deep neural networks has become a hot topic in machine learning and computer vision. Such an image can be generated at pixel level by learning from a large collection of images. Learning to generate colorful cartoon images from black-and-white sketches is not only an interesting research problem, but also a useful application in digital entertainment. In this paper, we investigate the sketch-to-image synthesis problem by using conditional generative adversarial networks (cGAN). We propose a model called auto-painter which can automatically generate compatible colors given a sketch. Wasserstein distance is used in training cGAN to overcome model collapse and enable the model converged much better. The new model is not only capable of painting hand-draw sketch with compatible colors, but also allowing users to indicate preferred colors. Experimental results on different sketch datasets show that the auto-painter performs better than other existing image-to-image methods.

Deep research and auto-generate knowledge relationship diagrams in PDF. From research to visualization in one tool. 深度调研并自动生成知识关系图谱PDF。

🎓 AI-powered PhD application outreach system — auto-discover professors, deep-research their work, compose personalized cold emails, send & track replies. Built with FastAPI + React.

My free implementation of @dzhng's implementation of OpenAI's new Deep Research agent. Get (almost) the same capability for free. You can even tweak the behavior of the agent with adjustable breadth and depth. Run it for 5 min or 5 hours, it'll auto adjust :)

My own open source implementation of OpenAI's new Deep Research agent. Get the same capability without paying $200. You can even tweak the behavior of the agent with adjustable breadth and depth. Run it for 5 min or 5 hours, it'll auto adjust.

Solar Power forecasting for a Solar Power System is a very active research field, as reliable information about the future power generation allow for a safe operation of the power grid and helps to minimize the operational costs. Deep Learning algorithms have shown to be very powerful in forecasting tasks, such as economic time series or speech recognition. Up to now, Deep Learning algorithms have only been applied sparsely for forecasting renewable energy power plants. By using different Deep Learning Algorithms, such as RNN,LSTM with different Feature extraction method like PCA,1D CNN , Auto encoders , My motive is to show the forecast strength of these algorithms compared to a standard MLP and traditional machine learning model in forecasting the energy output of 21 solar power plants.

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MEGA-OCTo-agent Deep researching database and action work flow with all permission and take API from ((DEEP MULTI TASKING WITH AUTO AND INDEPENDENCE UPDATE, WHICH HAVE ALL AND LAST UPDATED DOCUMENT FOR( ( CO-PILOT)(GEMINI 2.5 PRO)(CHAT GPT 5)(GROK4 SUPER)) WHICH INTEGRATE TO MIX A( XXXL MEGA BOT)

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**DeepResearcher** is a lightweight, API-free research companion that scours the open web and scientific archives to generate concise literature-style summaries on any topic — from *Agentic Economics* to *Neural Symbolic AI*. It’s designed for **independent researchers, students, and AI developers** who want quick, multi-source research briefs

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Deep Learning Research in Auto Insurance

My own open source implementation of OpenAI's new Deep Research agent. Get the same capability without paying $200. You can even tweak the behavior of the agent with adjustable breadth and depth. Run it for 5 min or 5 hours, it'll auto adjust.

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"Your Fully-Automated Personal AI Assistant, and Open-Source & Cost-Efficient Alternative to OpenAI's Deep Research"

Engineered an autonomous AI agent capable of performing multi-step web research to answer complex user queries in real-time.

Automatic deep research skill for Claude Code and AI agents. Multi-round search with multi-source verification, outputs structured reports. 自动深度研究技能。给 Claude Code 等 AI Agent 用的研究助手，通过多轮搜索和多源验证，输出结构化报告。

An AI-powered research assistant that autonomously investigates any topic using specialized agents, parallel web searches, and quality-controlled report generation.

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Welcome to this intelligent ResearchManager — an advanced AI-driven orchestration system that automates deep research workflows from query planning, web searching, report writing, to email delivery — all seamlessly powered by async agents!

Deep Learning-Based Method for 4 to 6-Digit CAPTCHA Recognition Using CNN + RNN

심층강화학습기반 디지털 트윈 환경에서의 자율주행 연구

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A multi-agent AI system that performs deep research on any topic — automatically plans searches, gathers data, writes a detailed report, and emails the results using OpenAI and SendGrid APIs. Built with Gradio, Python, and async architecture.