【AI最新動向 2026年2月6日】論文5件・GitHub5件

2026年2月6日2026年2月10日

📝 この記事のポイント

🚀 AI技術の最新動向 – 2026年2月6日世界中から収集したAI・機械学習の最新情報をお届けします 📑 目次 💻 注目のGitHubプロジェクト PACKIARAJ-R/ML-Image-Classification-using-CNN jmbarrancoml/awesome-european-ai marimo-team/modernaicourse Dipta04/Project_Machine_Learning SyedShaheerHussain/Anti_Phishing_Email_Detector_gui 📌 関連記事もチェック 📚 最新研究論文 1. Shared LoRA Subspaces for almost Strict Continual Learning 著者: Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari Adapting large pretrained models to new tasks efficiently and continually is crucial for real-world deployment but remains challenging due to catastrophic forgetting and the high cost of retraining. While parameter-efficient tuning methods like low rank adaptation (LoRA) reduce computational demands… 論文を読む → 2. Pseudo-Invertible Neural Networks 著者: Yamit Ehrlich, Nimrod Berman, Assaf Shocher The Moore-Penrose Pseudo-inverse (PInv) serves as the fundamental solution for linear systems. In this paper, we propose a natural generalization of PInv to the nonlinear regime in general and to neural networks in particular. We introduce Surjective Pseudo-invertible Neural Networks (SPNN), a class… 論文を読む → 3. DyTopo: Dynamic Topology Routing for Multi-Agent Reasoning via Semantic Matching 著者: Yuxing Lu, Yucheng Hu, Xukai Zhao Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns that are poorly matched to the stage-dependent needs of iterative problem solving. We introduce DyTopo, a manager-guided … 論文を読む → 💻 注目のGitHubプロジェクト 1. PACKIARAJ-R/ML-Image-Classification-using-CNN Built a CNN-based image classification system with data preprocessing, model training, evaluation, and result visualization using accuracy curves and confusion matrix for reliable image recognition. ⭐ 27 stars | 🔀 0 forks リポジトリを見る → 2. jmbarrancoml/awesome-european-ai A curated list of European AI companies, research labs, open source projects, and resources ⭐ 10 stars | 🔀 0 forks リポジトリを見る → 3. marimo-team/modernaicourse A companion to CMU professor Zico Kolter's Intro to Modern AI. Learn the basics of machine learning, then train your own LLM from scratch. ⭐ 8 stars | 🔀 0 forks リポジトリを見る → 4. Dipta04/Project_Machine_Learning HSC Result Predictor using Random Forest Regression to forecast student exam scores based on historical data and performance indicators. ⭐ 7 stars | 🔀 0 forks リポジトリを見る → 5. SyedShaheerHussain/Anti_Phishing_Email_Detector_gui Analyzes email content, headers, and links to identify phishing attacks, calculate risk scores, store history, and visualize ML evaluation results. ⭐ 7 stars | 🔀 0 forks リポジトリを見る → 📚 あわせて読みたい「プロンプトは戦略だ！」と学んで劇的効率UP！私のAI活用術私が実感！AIで物流の悩み解消、時間もコストも浮いた話【AI最新動向】一歩先の未来へ！私が触れた最先端AIの世界。

🚀 AI技術の最新動向 – 2026年2月6日

世界中から収集したAI・機械学習の最新情報をお届けします

📑 目次

💻 注目のGitHubプロジェクト
1. PACKIARAJ-R/ML-Image-Classification-using-CNN
2. jmbarrancoml/awesome-european-ai
3. marimo-team/modernaicourse
4. Dipta04/Project_Machine_Learning
5. SyedShaheerHussain/Anti_Phishing_Email_Detector_gui
📌 関連記事もチェック

📚 最新研究論文

1. Shared LoRA Subspaces for almost Strict Continual Learning

著者: Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari

Adapting large pretrained models to new tasks efficiently and continually is crucial for real-world deployment but remains challenging due to catastrophic forgetting and the high cost of retraining. While parameter-efficient tuning methods like low rank adaptation (LoRA) reduce computational demands…

論文を読む →

2. Pseudo-Invertible Neural Networks

著者: Yamit Ehrlich, Nimrod Berman, Assaf Shocher

The Moore-Penrose Pseudo-inverse (PInv) serves as the fundamental solution for linear systems. In this paper, we propose a natural generalization of PInv to the nonlinear regime in general and to neural networks in particular. We introduce Surjective Pseudo-invertible Neural Networks (SPNN), a class…

論文を読む →

3. DyTopo: Dynamic Topology Routing for Multi-Agent Reasoning via Semantic Matching

著者: Yuxing Lu, Yucheng Hu, Xukai Zhao

Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns that are poorly matched to the stage-dependent needs of iterative problem solving. We introduce DyTopo, a manager-guided …

論文を読む →

💻 注目のGitHubプロジェクト

1. PACKIARAJ-R/ML-Image-Classification-using-CNN

Built a CNN-based image classification system with data preprocessing, model training, evaluation, and result visualization using accuracy curves and confusion matrix for reliable image recognition.

⭐ 27 stars | 🔀 0 forks

リポジトリを見る →