tensorflow — An Open Source Machine Learning Framework for Everyone
TensorFlowはオープンソースの機械学習フレームワークで、誰でも使用できるように設計されている。
- 用途
- 人間に学習フレームワーク
- 難易度
- Easy
- コスト
- Medium
「supervised」の検索結果
210 件TensorFlowはオープンソースの機械学習フレームワークで、誰でも使用できるように設計されている。
pytorchはPythonでTensorや動的ニューラルネットワークを実装でき、強力なGPUアクセラレーションをサポートしている。
netdataは、チームに関係なくAIパワーで全システム観察できる最速のパスを提供している。
kerasは、人類が開発できる深層学習フレームワークで、モデル定義からトレーニングまでを行うことが可能。
juliaはJuliaプログラミング言語で、高速演算とパッケージ管理が可能である。
streamlitはStreamlitライブラリを使って、データアプリを作成・共有することができる。
ColossalAIは、より安く、速く、よりアクセスが容易な-large AIモデルの作成に適したフレームワークを提供します。
マシンラーニングシステムの理論と実装に関する本。
このライブラリは、3次元幾何学とモーションの解析のためのオープンソースライブラリです。このライブラリは、複数の視点からの画像を扱い、構造計算とマルチビューステレオの解析をサポートしています。
Diffusion models represent a powerful class of generative models known for their solid theoretical foundations
Semi-supervised medical image segmentation aims to train reliable segmentation models using limited labeled da
Semi-supervised cardiac image segmentation aims to exploit abundant unlabeled images together with limited ann
This paper presents an innovative guidance and control method for a space manipulator that actively maneuvers
Object rearrangement planning in cluttered environments is often non-monotone, requiring objects to be tempora
scikit-learnはPythonで機械学習を行うことができるライブラリで、データの分類・可視化・特徴量選択などが可能である。
このリポジトリでは、64MパラメータのGPTを完全にTrainingし、2時間以内に完成させる手法を提供します。
コンピュータビジョンのデータセット、変換、モデルのライブラリ。
CARLAは、オープンソースのシミュレータで、主に自動運転研究のために使われます。このシミュレータを使うことで、車両などのロボットをシミュレートし、様々なシナリオを実行できます。
機械学習とデータ分析のためのC++のツールキット。
このリポジトリでは、金融分野に適したLarge Language Modelsを提供しています。
FiftyOneは、データセットの精査とAIモデル可視化を支援するライブラリです。このライブラリは、データセットの品質を高め、AIモデルを可視化するのを支援するために使用できます。
LLMの推論 Transparency を高めるために、DiffusionGemmaの計算を分離しVariable Transparency とAlgorithmic Transparencyを評価します。
ベクトル検索と構造化されたフィルタリングを組み合わせたベクターデータベースです。
この研究では、自然言語処理の負担を減らすモジュラリティを目指しています。モジュラリティとは、システムを小さくて独立した部分に分割して、それぞれを簡素化することです。この研究では、文脈に応じてモジュラリティを変更できるメカ
テキスト分析、センチメント分析や単語分割などを行えるライブラリ。
Real-world problems span diverse domains, including program synthesis, symbolic reasoning, planning, and optim
Offline multi-task reinforcement learning (MTRL) aims to learn a unified policy from heterogeneous offline dat
Modern high-performance computing (HPC) clusters integrate multi-generation CPUs and GPUs, which generate rich
We study the numerical constructions of almost complex and complex structures on spheres and products of spher
Communication is important for our well-being, but it can be impaired by disabilities, such as locked-in syndr
Graph forecasters for sensor networks are trained in one regime and deployed in others, where sensor coupling
Despite their widespread success across machine learning, the learning dynamics and generalization properties
Robust machine learning for graph-structured data has made significant progress against test-time attacks, yet
While structural and functional magnetic resonance imaging (sMRI, fMRI) offer profound potential for researchi
A model pretrained to predict a customer's next event can estimate the probability of future events without tr
In node selection tasks, the goal is to identify a single unknown target node in a graph. We consider probabil
Full Waveform Inversion (FWI) is a fundamental inverse problem in geophysics to estimate subsurface properties
Battery degradation remains a central challenge in the development and broad application of sustainable energy
Large language models (LLMs) have introduced a generative approach to recommendation, producing item lists fro
Spatial multi-omics technologies jointly profile diverse molecular modalities with spatial context, providing
Recent works have observed implicit cross-modal alignment between independently trained unimodal models. Howev
We develop PanelGP, a conditional factor model for large panels of stock returns in which firm characteristics
Foundation models in changing environments can encounter unfamiliar domain knowledge that their original train
Small language models (<=9B parameters) can support local medical question answering (QA) while reducing priva
Skin cancer diagnosis, particularly differentiating melanoma from benign nevi, is challenging due to the visua
Third-party Agent Skills extend what an autonomous agent can do, but a malicious Skill can hide data exposure
Instruction tuning for multi-task network traffic analysis requires data with clearly defined sources, supervi
Text-to-SQL translates natural language questions into SQL queries, enabling database access without writing S
Embodied agents are increasingly deployed in open-world environments, yet current robustness evaluations remai
We introduce Axion 1.0, a fully open agent foundation model that combines strong and broad agentic capabilitie
New federal legislation will require states with high payment error rates in the Supplemental Nutrition Assist
Personal AI agents are increasingly capable of handling long-horizon tasks across applications, yet users ofte
Self-supervised learning inherits the coverage of its source data. When an unlabeled corpus is long-tailed, th
Remote sensing image fusion and semantic interpretation are usually optimized separately, so reconstruction qu
Reclamation of saline-alkali land requires management plans that account for soil and water conditions, treatm
Speculative decoding (SD) accelerates large language model inference by reducing the sequential cost of token-
Language model agents often struggle with complex tasks even when equipped with expert-written skills. Such sk
We introduce Dory1.0-4B, a 4-billion-parameter looped (latent-recurrent) language model with elastic depth: a
ufakzeka-kulak is an open Turkish speech-to-text model of 31.6M parameters, a FastConformer encoder with a tok
Complex documents such as scientific papers contain rich information in tables, figures, and equations; howeve
Prompt compression is aimed at reducing input prompt lengths to enable cheaper, faster, and potentially higher
The author shows a methodology for constructing a network map of the artworld. The tweets posted by a manually
Large language models (LLMs) have achieved strong performance across diverse tasks, from question answering to
Steering vectors align a model at inference time without touching its weights, but eliciting several personas
Scientific discovery from the literature requires assessing connections among findings obtained under differen
Programs that use a language model as a classifier act on its most probable label. Text injected into the inpu
Dialectal Arabic speech recognition remains constrained by the scarcity of dialect-resolved transcribed speech
State-of-the-art bronchoscopy guidance systems and computer-aided diagnosis methods have emerged as important
Learning from human data offers a scalable path toward embodied intelligence, yet it requires models to accura
Foundational vision models have become the de facto standard for many vision tasks due to their strong perform
Autonomous mobility is essential for sustained lunar surface operations, as communication delays and line-of-s
Accurate mapping of shallow-water environments using unmanned aerial vehicle (UAV) imagery is challenged by wa
Multi-source remote sensing data classification has received growing attention recently. However, existing met
Accurate full-body tracking in Virtual Reality (VR) is heavily underconstrained when relying solely on consume
Humanoid rigging for modern characters with complex garments remains challenging due to the need for dense aux
Understanding how objects and their spatial relationships evolve in 3D space over time remains challenging for
Supervised low-light image and video enhancement has achieved remarkable progress, yet current models remain f
One of the contributing factors to the continuing debate among art historians over the use of computational me
Hyperspectral videos provide rich spectral signatures for robust tracking under challenging conditions such as
Hyperspectral image (HSI) classification requires the representation of contiguous spectral signatures and spa
Computed tomography (CT) provides diverse patient information and various clinical tasks, for which numerous d
Ball-balancing robots (ballbots) must lean to accelerate, and the lean is limited by the wheel torques and by
Virtual reality experiments involving navigation and simulated robot motion often require large, realistic env
Fine-grained manipulation couples instruction grounding, local visual precision, and sustained execution. We p
Collision-free reaching is central to manipulation, yet real cells often leave the size and exact position of
Agentic Real2Sim2Real systems can reconstruct a scene in simulation from camera observations, but contact-rich
Control barrier functions (CBFs) are a standard way to keep a planner inside a safe set, but they assume contr
A competent learned controller already recovers from many disturbances. Improving it means learning a correcti
Touching a virtual agent involves more than detecting a finger on a display: the contact surface can deform an
This study aimed to examine the impact of finger movements in hugging robots on users by experimentally invest
We study the efficiency of Bayes-Nash equilibria in first-price procurement auctions. We measure efficiency by
Social choice literature on multiwinner elections tends to focus on characterizing two distinct tasks: majorit
OpenBBは、分析家・量算家・AIエージェント用の金融データプラットフォームを提供している。
photoprismはAIパワーで管理される写真管理アプリケーションで、写真の特徴や情報を自動的に検出することができる。
このリポジトリは、Natural Language Toolkit(NLT)のソースコードを収録しています。
最新のマシンラーニング研究論文を紹介している。
ModelScopeは、モデルをサービス化するためのプラットフォームです。モデルを作成し、ホスティングし、管理し、配信することができます。
An invertible graph aggregation preserves the complete feature table, but can increase the size of a classifie
Language and vision models became data-efficient by pretraining on plentiful unlabelled data; physical field m
Training a classifier means letting a validation metric decide which model is kept and when training stops. A
AI reviewers are increasingly used to assess scientific manuscripts, yet it remains unclear whether their judg
LLM agents are increasingly deployed in Multi-Agent Systems (MAS), and they introduce the risk of coordination
Social media translation requires preserving meaning while capturing the cultural nuances of user-generated co
Simulated students offer a scalable way to test learning platforms and AI tutors before deployment with real s
LLM-based role-playing agents are fluent at imitating a character's style, yet struggle to make role-consisten
Depression affects millions of Bengali speakers across South Asia, yet automated detection systems have relied
Accurate house price prediction is essential for real estate buyers, sellers, agents, and financial institutio
Calculating inter-annotator agreement is an established practice in NLP, and disagreement-aware work increasin
Robust segmentation of biomedical images remains challenging primarily due to ill-defined object boundaries. A
Task-optimized deep neural networks have risen to prominence as the most predictive phenomenological models of
Vision-language models (VLMs) suffer from visual hallucination, such as saying an object that is not present i
Robust 4D reconstruction of deformable endoscopic scenes from monocular videos remains challenging due to non-
In modern robot learning, generative robot policies are first pretrained through supervised learning from demo
This paper studies dual path following for a quadrotor carrying a three-degree-of-freedom arm. The center of m
Surface cleaning requires robots to adapt both where they clean and how they interact with contamination whose
Scaling computer-use agents from individual actions to complex software work requires experience that connects
We study hybrid online learning with stochastic features and adversarial labels when the feature distribution
User simulators generate responses in place of human participants, allowing researchers to estimate the result
Hao Ren, Shuohan Chen, Senyuan Mu, Ruihan Huang, Wanfeng Shang, Yajing Shen
Long-horizon embodied manipulation requires policies to act on information that is no longer visible. Modified
We study approximate Nash equilibria in nonatomic congestion games, with the goal of understanding how much th
マシンラーニングの入門コースを提供する。
このリポジトリはコンピュータサイエンスのビデオコースの一覧を提供しています。
データサイエンスの学習には役立つリポジトリ。実世界の問題に応じた学習が可能。
Concept erasure is a prominent approach to achieving fairness in machine learning through the removal of sensi
Data-driven learning for the solution operator of a differential equation has broad scientific importance, but
This paper presents a neural network model for storing and recalling color images of different sizes using the
Data flywheels promise continuous improvement via insights from deployment data. Understanding how the deploye
Uncontrolled hemorrhage remains a leading cause of preventable trauma mortality. Timely intervention is not al
Recent developments in both high-thrust (HT) and low-thrust (LT) propulsion technologies broaden design option
Unified Multimodal Models (UMMs) achieve remarkable success on diverse multimodal understanding and generation
Short-video search needs compact query rewriters that recover users' personalized intent from ambiguous querie
クエンティング投資プラットフォームを実現するためにAI技術を活用します。
google-researchはGoogle Researchで、研究者がアクセスすることができる機械学習リソースの一つである。
AIモデルを高速にトレーニングするためのライブラリ。1台から10000台のGPUで利用可能。
Omniprediction concerns the task of making predictions that are simultaneously accurate with respect to differ
Modern data analysis pipelines increasingly rely on large datasets assembled through retrieval, scraping, auto
We establish structural properties of the nonparametric maximum likelihood estimator (NPMLE) for $d$-dimension
Self-supervised contrastive learning (SSCL) learns representations by contrasting augmented views of the same
Parameter estimation and classification in binary logistic regression deteriorate severely when the number of
Learning a shared subspace in multitask learning is an important statistical problem, yet exact rates remain p
Formula-Driven Supervised Learning (FDSL) enables vision pre-training without real images, but existing method
A capable voice assistant must do more than recognize words; it must understand requests, reason over context,
Across coding, web, and tool-use tasks, language-model agents are now routinely trained with the same recipe:
Foundation models are typically trained in stages: pretraining, midtraining, supervised fine-tuning (SFT), and
While frontier vision-language models demonstrate strong capabilities in user interface (UI) navigation, their
この論文では、予測性維护と健康管理のための大型言語モデルが使用されます。この modelは、故障診断や寿命予測などの問題を解決するように設計されています。
Gymnasiumは、シングルエージェントRLの疑似環境を提供するAPIです。
Principal-agent hypothesis testing studies statistical contracts in which a principal rewards an agent accordi
この研究では、重症看護病棟内の気流と光など環境要因が気性変化の予測に利用できるか検討した。その結果、日照時間と音圧レベルを考慮すると、気性変化の予測精度が向上した。
Bounds based on Integral Probability Metrics (IPMs) are ubiquitous in machine learning and statistics, appeari
Modern machine learning models are often trained on large datasets assembled from many different sources, whos
Deep neural networks learn data-dependent features, a capacity widely credited for their empirical success. Ho
Objective: Variable selection for clinical prediction models is commonly done on statistical grounds related t
Dimension-reduction methods such as PCA identify a subspace capturing most of the variation in the data, but n
Statistical graphical models are representations of the dependences between the components of a random vector.
Traffic forecasting requires modeling complex temporal dynamics and the spatial dependencies imposed by road t
When allocating indivisible goods, the maximum Nash welfare rule is known to be the unique welfarist rule sati
Metis is a bet that better data, better training methods and new architectures can buy what a bigger parameter
Scaling supervised training for working agents requires diverse professional tasks that yield reliable expert
spaCyはPythonで動くIndustrial-strength Natural Language Processing(Language理解の高度なライブラリです。文脈理解、構文解析、名詞の抽出など、複雑なNLPタ
Mathematical Foundations of Reinforcement Learningは、ディープラーニングにおける推論力学習の数学的基礎を網羅している。
Lightning routing nodes lend their channel balance for a posted fee. Operators' tools move that fee with the b
このリポジトリでは、LLMベースのエージェントアプリケーションのための強化学習の橋渡しを提供しています。
中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
We study capacity modification in the Hospitals/Residents problem with Couples, in which hospital capacities a
It is well-known that under nominal communication, where agents are able to share information with one another
In this paper, we identify level-$k$ reasoning in repeated games that operates at the level of a supergame str
OpenCVを用いて画像処理の学習方法を紹介している。
Recent electroencephalography (EEG) foundation models increasingly emphasize model scale, potentially limiting
The nucleon is the multiplicative counterpart of the nucleolus: it lexicographically maximizes the fraction of
The modeling of the behavior of agents in strategic environments and the prediction of the resulting outcomes
Smart-city applications often combine scarce labeled data with abundant unlabeled observations. Semi-supervise
We study the parameterized complexity of finding an EF1 allocation of indivisible items in the group-sharing s
We study randomized committee elections with additive preferences, where we seek best-of-both-worlds proportio
We show that computing an approximate correlated equilibrium of a polytope game is PPAD-complete, and thus pol
Given an incentive-compatible mechanism for a single agent on a restricted domain of valuations, we consider i
A course in reinforcement learning in the wild
Is there a fundamental tradeoff between desiderata for safe AI systems, such as harmlessness and helpfulness?
Allocating renewable resources fairly requires accounting for how present decisions affect future availability
For every fixed $\varepsilon\in(0,1)$ and $η\in[0,1)$, we prove that computing an $(\varepsilon,η)$-weak appro
We give the first unconditional family of polynomial-time algorithms that breaks the $1/3$ approximation barri
We study simple auctions for one additive buyer whose values for $m$ items are independent. Write $\mathrm{REV
Open-ended search combined with foundation models has produced advances such as faster algorithms, new results
How does post-training change cooperation during repeated interaction? Within each of seven released model lin
Automated market makers (AMMs) are central to decentralized exchanges, but their reserve curves make mechanism
In the classical principal-agent setting, the principal delegates some task to the agent, who receives a payme
The Value Problem for weighted timed games, an extension of timed automata with weights and adversity, consist
Vowpal Wabbitは、機械学習を進歩させるためのオンライン学習、ハッシュ、reduceなどの強力なアルゴリズムを含むシステムです。その結果、さまざまな問題に応じて、高品質な解決策を提供できます。
面倒なシーケンスデータ処理を自動化するツールであるChiplingoが提案されました。
We consider two linked problems for ranked choice elections: building a compact summary of a preference profil
We study the route-set allocation problem between end nodes in capacity-constrained flow networks with transfe
Accord is an arbitration oracle on Solana. Any Solana program can create an application specific court (i.e.
Poset games form a fundamental class of combinatorial games that includes classical games such as Nim and Chom
P
We study the fair allocation of indivisible items among $n$ agents with additive valuations (or costs) using t
Relying on manipulable characteristics to target the allocation of resources is fraught with difficulties. Nai
We study a truthful facility location problem in which agents have private positions in a metric space and kno
We study the unit-demand pricing problem under \textit{min-buying} behavior, where customers purchase the lowe
このリポジトリは自然言語処理(NLP)に関するリソースをまとめたものです。
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects,
GUI for a Vocal Remover that uses Deep Neural Networks.
Landscape analysis has been successfully applied to understand complex optimisation problems, gain insights in
Deploying a pretrained controller exposes it to conditions that are absent from its training data. Sensor drif
This paper presents a construction of a small universal machine within the framework of Multi-set Reaction Sys
The Capacitated Vehicle Routing Problem (CVRP) remains a central concern in logistics research, as route optim
End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordinat
Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models
Neuromorphic spiking neural networks (SNNs) offer a promising alternative to conventional deep neural networks
We propose a new spiking neural network (SNN) design to process static images and event streams using time-to-