Category
画像分類、検出、セグメンテーション、動画認識など、視覚AIの実装と評価に関係する技術群です。
ultralyticsはYOLO(You Only Look Once)の技術を使用したオブジェクト検出ライブラリで、高い精度を提供している。
YOLOv5という物体検出アルゴリズムをPyTorchから他の言語に変換できるライブラリ。
supervisionは、機械学習技術を活用して、ユーザー独自のコンピュータビジョンツールを作成することができる。
ultralyticsはYOLO(You Only Look Once)の技術を使用したオブジェクト検出ライブラリで、高い精度を提供している。
データラベル化と注釈化を行うためのツールです。
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。
ultralyticsはYOLO(You Only Look Once)の技術を使用したオブジェクト検出ライブラリで、高い精度を提供している。
データラベル化と注釈化を行うためのツールです。
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。
CoreNLPはJavaで開発されたNLPツールのセットであり、分割、文分割、名詞認識、パーシング、コorefence、感情分析などを行える。
stanzaは、さまざまな言語を処理するための言語処理用ライブラリです。
Tokenization is a fundamental component of modern language models: before a model sees data, its tokenizer has
Motivated by the expressive power of neural ordinary differential equations in flow-based generative modeling,
Deep-learning-based mass detectors usually downsample mammograms, trading fine image detail for lower computat
Reasoning vision-language-action (VLA) models pair physical control with natural-language rationales that supe
Speech watermarking is becoming a key defense for digital copyright and content authentication. Existing attac
Why do language models fail on long inputs? The common answer is length.
Parallel decoding speeds up masked diffusion language models by writing several tokens per forward pass. Publi
Camera object detectors lose recall in rain, fog, snow and sand, and the confidence threshold at which a detec
Chest radiography (CXR) diagnosis is critical for thoracic disease assessment, yet challenged by the need to i
Semi-supervised medical image segmentation aims to train reliable segmentation models using limited labeled da
Counterfactual sketch animation explores how a static sketch evolves under a hypothetical intervention. We pre
Semi-supervised cardiac image segmentation aims to exploit abundant unlabeled images together with limited ann
Online 3D Gaussian mapping enables fast and high-fidelity novel view synthesis, with broad applications in aug
The corotation radius R_CR of a spiral galaxy marks the radius where the angular speed of the spiral pattern m
Hamilton-Jacobi (HJ) reachability provides certified backward reachable tubes (BRTs) for safety-critical robot
supervisionは、機械学習技術を活用して、ユーザー独自のコンピュータビジョンツールを作成することができる。
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。
CVATは、機械学習用の業界標準のデータエンジンです。さまざまなスケールのチームが使用し、さまざまなスケールのデータに対応しています。
イメージを注釈するツール。ポリゴン、長方形、円、線、点などを注釈することができる。
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。
ノードベースのビジュアルプログラミングツールです。
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。
データをロギング・ストーリング・クエリして視覚化できるSDKです。
3D点群処理のためのライブラリであるPoint Cloud Library（PCL）。
The uncertainty of a statistical model is most commonly factorized into an aleatoric and an epistemic part. Th
Autonomous vehicles require robust perception systems to operate safely under diverse environmental conditions
Graph forecasting systems often rely on prediction intervals to quantify uncertainty across connected location
Neural controlled differential equations (Neural CDEs) evolve hidden states along continuous paths constructed
Retaining predictive gains can require persistent errors in a model's response to interventions. For determini
Mapping the three-dimensional distribution of dark matter is key to tracing the growth of cosmic structure. Tw
In this paper, we study when two parties should pool their data to train a machine learning model. Two agents,
For effective resource management, infrastructure planning, and sustainable tourism, it is really important to
Hybrid models and neural differential equations (NDEs) are becoming increasingly important for modelling physi
Hamiltonian neural networks provide a principled framework for learning conservative dynamics. A scalar Hamilt
Deep learning models for electronic health records achieve strong predictive performance but provide little in
Recent language model (LM) safety failures have largely been studied as disparate phenomena. In agentic misali
**Purpose:** Ultrasound biometry is widely used across various clinical applications, including prenatal and c
Suicide prevention remains a critical public health challenge, and electronic health records (EHRs) provide an
Calibrated multiaccuracy asks that a predictor be globally calibrated and multiaccurate with respect to a boun
Inverse Reinforcement Learning (IRL) aims to recover expert rewards that transfer across environments with dif
In node selection tasks, the goal is to identify a single unknown target node in a graph. We consider probabil
Artificial Intelligence, and Machine Learning in general, is becoming pervasive across all domains and discipl
Diffusion models trained on distinct datasets can produce highly similar samples when prompted with the same n
An aggregate task score does not distinguish failures of scheduling, state retention, and candidate selection.
Recourse-aware learning trains models so that people who receive an adverse decision can reverse it with an af
On July 1, 2025, Vietnam reduced its 63 provinces to 34, abolished its 696 districts, and replaced its 10,035
There are many causal discovery algorithms, but few guiding principles for choosing between them. Methods are
Pose-driven human video diffusion animates a person from a single reference image and a target pose sequence,
While state of the art for image and video generation, the fundamental reasons for the effectiveness of genera
Fusing independently normalized attention heads can increase the number of explicit key-value entries, or atom
Dynamic regret measures an online learner against a moving comparator, and standard analyses assume the learne
Learning to stabilize an unknown continuous-time stochastic linear system is a central problem in control theo
Increasingly complex neural models predict blood-oxygen-level-dependent (BOLD) responses to naturalistic stimu
The Musical Metaverse (MM) enables geographically distributed musicians, audiences, sound engineers, and AI ag
A stored experience may answer one future question and offer little help with another. We measure this task-co
Financial research agents can generate and monitor trading rules faster than a human can document the resultin
Novel imaging modalities promise improved diagnostics, but AI development is constrained by scarce training da
The literature on autonomous weapon systems (AWS) includes many proposed definitions for these (types of) syst
Kolmogorov-Arnold Networks (KANs) have recently been proposed as a promising alternative to Multi-Layer Percep
Reaction data underpin machine learning for reaction prediction, condition recommendation, and retrosynthetic
Robust driver-state modelling requires synchronized physiological, behavioural, and contextual signals, yet ex
Law changes over time. A court decides a case under the law in force on that day, and legal QA benchmarks grad
WhatsApp lets a business send free-form messages only within 24 hours of a user's last message; outside this c
Automated liver ultrasound report generation improves the diagnosis of liver diseases by producing clinically
Language models with similar benchmark accuracy can succeed on different items. Overall scores do not show whe
Tool-using language-model agents often execute actions that their domain policies forbid. We present LeanGuard
We describe our approach to the V2X-Real track of the UrbanTwin Sim2Real LiDAR Challenge, in which a 3D object
We describe our approach to the LUMPI track of the UrbanTwin Sim2Real LiDAR Challenge, in which a 3D object de
Autonomous mobility is essential for sustained lunar surface operations, as communication delays and line-of-s
Parametric human body models such as the Skinned Multi-Person Linear (SMPL) model provide compact representati
Multimodal test-time adaptation (TTA) enables pretrained multimodal models to accommodate distribution shifts
Most image-based 3D reconstructors primarily recover visible surfaces, producing partial point clouds with lar
Fingerspelling - the sequential signing of letters that compose proper names, technical terms, and out-of-voca
Image-text corpora contain copies of one image, captions that describe one image in different ways, captions r
Accurate full-body tracking in Virtual Reality (VR) is heavily underconstrained when relying solely on consume
We present a GPU-native volumetric-video system for real-time reconstruction of graphics-compatible textured t
Humanoid rigging for modern characters with complex garments remains challenging due to the need for dense aux
Infrared and visible image fusion integrates complementary information from both modalities to provide a more
Adapting features before upsampling can improve dense prediction, but the gains may arise from changes in feat
End-to-end autonomous driving policies require effective visual representations that capture both spatial scen
3D Gaussian Splatting (3DGS) enables photorealistic novel- view synthesis with real-time rendering, yet fine-g
This paper studies what subspace representations contribute to synthetic-to-real transfer in 3-D surface inspe
Semantic granularity, which refers to the levels at which visual representations organize image content into m
Widespread image sharing on social media has increased the need for visual privacy recognition to identify ina
3D Gaussian Splatting (3DGS) has shown considerable potential for novel view synthesis (NVS) and 3D reconstruc
One of the contributing factors to the continuing debate among art historians over the use of computational me
Reconstructing detailed geometry and realistic appearance from a single RGB image is essential yet fundamental
Hyperspectral videos provide rich spectral signatures for robust tracking under challenging conditions such as
3D semantic occupancy prediction provides dense geometric and semantic scene representations for autonomous dr
World-action models (WAMs) use video-generation priors to jointly predict future observations and robot action
Reinforcement learning (RL) post-training improves the single-sample quality of visual generative models, but
Cross-view object correspondence (CVOC) aims to establish associations of the same target between query and se
Understanding how cells respond to perturbations over time is central to cell biology and drug discovery. Live
A mobile manipulator asked to "put the toys away in the toy box" must decide which objects are toys and which
World action models (WAMs) jointly generate actions and imagined futures, but a plausible prediction need not
Conventional robot arms can be extremely heavy compared with the everyday objects they manipulate, creating a
Overactuated multirotors can produce the same wrench with many rotor-speed combinations, some of which leave t
Pre-touch sensing, or sensing information about an object before contact, is an attractive modality for robot
A robot that acts around people needs a world model of the human: a belief over the person's body state and a
Many manipulation goals are easier to visualize than to specify numerically through explicit geometric constra
Soft robot co-design methods can jointly optimise morphology and control, but the resulting designs are often
This paper presents a decentralized guiding vector field framework for rigid formation path following in multi
Autonomous robots are gaining traction in off-road environments, driven by their rising demand in agriculture,
The Generalized Singular Value Decomposition (GSVD) is a central tool for comparing two linear operators that
Recent advances in Vision-Language-Action (VLA) models have enabled fine manipulation capabilities, yet perfor
Hierarchical control scales robot behavior by separating task-level planning from low-level control. In dynami
Purpose: Blended augmented reality (AR) overlays can provide ambiguous depth cues in which subsurface anatomy
Robot policies still fail at everyday manipulation: an unfamiliar task, an object never held before, a scene t
To design platforms for multi-operator mobility markets coordinating their operations or infrastructure to sup
Progress in AI is often measured by what a single model can do on its own. Yet teams of AI agents are starting
Science experiment videos demonstrate how experiments are performed, but offer no direct interaction for learn
We consider classification in high-dimensional feature spaces where only a vanishing fraction of features are
Spectral shrinkage encompasses a broad family of estimators for high-dimensional linear regression that regula
We study finite-horizon reinforcement learning with a safety constraint on the probability of reaching a failu
Tensor factor models provide low-dimensional representations of tensor-valued observations while preserving th
Convex regression provides a flexible nonparametric estimation framework while incorporating appropriate shape
Conditional sampling is central to Bayesian inference, generative modeling, and causal inference: given a join
We present a generalized variational approach for constructing energy-stable macroscopic partial differential
Scaling laws predict the outcome of large, expensive training runs by extrapolating trends from smaller, cheap
Key-value (KV) cache eviction methods rank tokens by attention scores, and each layer scores its own cache. To
Coding agents can destroy data, leak secrets and message the wrong person faster than a human can review. Coul
Factual recall in language models is typically framed as retrieving a factual association: a subject--relation
Temporal Knowledge Graph Question Answering (TKGQA) requires language model agents to retrieve evidence, selec
Anticipating financial outcomes requires synthesizing evolving evidence and reasoning under uncertainty, makin
Visual-text compression renders long contexts as images and is engineered around how much of the text a vision
We present See, Think, Use, a protocol that traces each answer of a vision-language model to perception, reaso
Monocular depth estimation aims to predict depth maps from single RGB images (forgoing the need for stereo cam
Robot foundation models now act in a closed loop, yet their safety is evaluated one variation at a time: robus
Diffusion driving vision-language-action models repeatedly execute the backbone at every denoising stage, incu
Monocular semantic SLAM aims to reconstruct scene geometry and build semantic maps from RGB observations. Exis
RL locomotion policies trained under nominal simulation conditions may encounter distribution shifts that comp
In human-robot co-manipulation, the robot's trajectory should accommodate the human's, where human sensorimoto
Latent-space path planning (LSPP) compresses the configuration space of a robotic manipulator into a compact,
Vision-language-action (VLA) models can generate task-oriented robot actions, but they do not guarantee safe e
Vision-language-action (VLA) models predict chunks of future actions, yet deployed robots waste time in two wa
Prediction errors from video world models are often treated as physical surprise, but they can also reflect ap
YOLOv5という物体検出アルゴリズムをPyTorchから他の言語に変換できるライブラリ。
Bayesian inverse problems require both informative prior models and computationally feasible posterior inferen
Learning from extensive longitudinal clinical records--spanning repeated encounters, evolving conditions, and
Replacing the matrix in an iteration with random low-rank matrices can reduce the cost of matrix-vector multip
Machine learning can screen far more candidates than can be experimentally validated, creating a need for sele
Calling a tool through generated text adds decoding steps, even when the computation itself is short. We study
Cross-country sentiment analysis faces three fundamental challenges: language-specific biases distort comparis
Post-trained language models fabricate citations at high rates. We ask whether that is reward hacking: scoring
Humanoid robots operating in shared, dynamic environments must respond to rapidly approaching objects while ma
Simulation-based VLA evaluation often treats matching task, seed, and episode identifiers as sufficient eviden
Accurate posture feedback is essential for precise control of continuum robots. Off-the-shelf bend sensors mea
Imitation policies inherit the operator's pace, and re-timing the demonstrations to run faster works only unti
The absolute trajectory error (ATE) is the standard measure of camera-motion accuracy, from SLAM to feed-forwa
Computing equilibria is a fundamental algorithmic problem in game theory and economics. Although general frame
We study finite sample guarantees for transport based mutual information estimation. Mutual information can be
Concept erasure is a prominent approach to achieving fairness in machine learning through the removal of sensi
Large generative models are commonly trained on data collected from the open web, which may contain data produ
Distributionally robust optimization (DRO) minimizes worst-case risk under distributional uncertainty, but its
World action models (WAMs) learn latent variables from observations and use these to both predict the evolutio
Sampling from Boltzmann distributions is a fundamental problem in physics, chemistry, and biology. We introduc
Implicit priors given by Gaussian denoisers successfully regularize a wide range of inverse problems in approa
Flow matching depends critically on the coupling used to pair source and target samples. Optimal transport (OT
We study the general problem of estimating $D(\dde(S))$, the probability that an unknown distribution $D$ assi
We study whether a language model can help design controllers whose behavior can be formally checked. In proof
Data flywheels promise continuous improvement via insights from deployment data. Understanding how the deploye
This paper introduces \emph{catenary visibility}, a new geometric visibility concept for a robotic system cons
Held-out validation loss is the standard offline signal for choosing checkpoints and comparing models, but its
Automated endoscope guidance reduces the need for continuous manual camera control during minimally invasive s
Embodied surgical AI requires reliable multimodal data, yet surgical data collection remains costly, difficult
How to reuse a pretrained locomotion policy for precise loco-manipulation is still an open problem. We propose
Scaling humanoid motion foundation models is constrained by the scarcity of diverse, robot-executable data and
Autonomous surface vessels operating in urban waterways must coordinate with other vessels in confined spaces
We study the online fair division of indivisible chores among $n$ agents under upgrade recourse, where earlier
Motivated by a broad literature in psychology, organizational behavior, and matching markets, we introduce str
Statistical contracts reward experimenters according to the evidence produced by a costly study, so the reward
Unityを使用してマシンラーニングエージェントを訓練して訓練できるツールです。
Modern data analysis pipelines increasingly rely on large datasets assembled through retrieval, scraping, auto
We study high-dimensional integration on bounded convex domains. Given a non-negative integrand $r$, the goal
Predictive models trained at well-resourced data-rich institutions often fail when deployed in new populations
We consider the problem of finite-sample identification of an unknown LTI system from a finite hypothesis clas
We study high-dimensional nonparametric regression under multisource covariate shift, where $\mathrm J$ source
In this work, we formalize the concept of intrinsic dimension of objective landscapes introduced in Li et al.
A streaming estimator must compute from the evidence that fits in memory. We determine when storing an accurat
Reinforcement learning with verifiable rewards (RLVR) makes a language model solve more problems on the first
Parameter estimation and classification in binary logistic regression deteriorate severely when the number of
Hardware-accelerated spiking neural networks (SNNs) implemented on memristive crossbar arrays offer significan
Classical theory predicts that irrational traders lose money to rational traders and are eventually driven out
Vision-Language-Action (VLA) models have demonstrated promising capabilities in robotic manipulation by integr
Do research agents have taste, the judgment of which experiments are worth running before their outcomes are k
Agentic image editors decompose complex requests into steps, but when a step fails, they mostly retry with the
We present PhysInsert, a framework for physically plausible reference-based object insertion that jointly adap
OpenWorldLibは、進化する世界モデルを提供する統一されたコードベースです。
Learning independence is fundamental to statistical inference and machine learning, yet learning independence
Particle Gibbs samplers with backward sampling are widely used for sampling the smoothing distribution of stat
Allowing for small fraction of errors in retrieved stored binary patterns, Hopfield-Hebbian neural network (NN
When exact probabilities cannot be computed, \emph{density ratio estimation (DRE)} is a key subroutine in the
Can a Watershed transform, the classical tool of morphological segmentation, be placed at the end of a deep ne
Music audio generation spans instrumental clips, full songs with vocals, edits of existing recordings, and sys
Humans routinely consume multimodal content, where textual and visual information is naturally interleaved. Al
We present EasyProver, a Lean proving system built from recursive agents with isolated contexts, asynchronous
Generative flows can admit different velocity fields that induce the same continuous marginal evolution but be
The short-time Fourier transform (STFT) characterizes the local frequency content of time-varying signals by e
An input skip can reduce reconstruction error while leaving a model's distribution of new samples unchanged. F
Density estimation with generative models is a common task in the physical sciences, for example in background
We study the computational limits of clustering $n$ observations drawn from a mixture of $K$ isotropic distrib
Model discrepancy may prevent a single calibration parameter from reproducing a physical response across the c
Mutual information (MI) is fundamental to representation-learning analysis in deep networks, but in high dimen
Dimension-reduction methods such as PCA identify a subspace capturing most of the variation in the data, but n
Audio systems aim to maximise the listener's perceived quality, traditionally evaluated through mean opinion s
We describe the agent we submitted to the GLEE Competition, which plays bargaining, negotiation, and persuasio
Token systems support repeated service exchange without monetary transfers, but their viability depends on the
Recent work has shown that, in zero-sum games, an optimizer can extract $Ω(\sqrt{T})$ strategic surplus---cumu
We study facility location in multidimensional normed spaces with the objective of minimizing social cost, the
We develop a unified framework for assortment optimization and matching under multinomial logit (MNL) choice,
We study fair division of uncertain items, where the utility of each item is a random variable whose realizati
We study the order-selection prophet inequality. A gambler knows the distributions of independent nonnegative
An action seen once and the same action seen three times receive the same action-recognition label, so that su
Generating videos of a specific subject from a few reference images remains challenging when the camera reveal
Physical wave processors are constrained by diffraction, but the bandwidth of the mathematical functions they
We study online fair division of indivisible goods among $n$ agents with frequency predictions: before any goo
Benade et al. (EC 2024) introduced a semi-random model for non-additive fair division in which each agent star
Generative AI interfaces can insert sponsored content at multiple points in an answer, where click-through rat
Position auctions require assigning advertisers to positions and determining their display order. Under cascad
Attribution for a time-series forecaster should answer two questions that a feature-level scalar cannot: when
We study optimal intervention design problems aimed at minimizing the aggregate volatility in network systems.
We study preemptive single-machine scheduling with predictions, where a prediction of the order of the jobs (o
The Perception-Adjusted Luce Model (PALM) introduced by by Echenique et al. (2018) is a sequential choice mode
Transactions differ in how their value changes with execution time and relative position. Ethereum's EIP-1559
In recent years, agentic orchestration has been widely applied to solve complex human tasks. However, existing
OpenCVを用いて画像処理の学習方法を紹介している。
この作品は机械学習の論文を100行のコードで実装する方法について説明しています。
Neural network models are increasingly constructed from synapse-resolution connectomes, and the same circuit i
We consider the problem of allocating indivisible goods to agents with additive valuations, under two classic
We study the best-response dynamics in games with random payoffs. We consider two-player bimatrix games, with
In the classical necklace splitting problem, beads of different colors lie on a line, and the goal is to divid
Architectural and structural design optimization in parametric software affords about a thousand evaluations o
このプロジェクトは２Ｄおよび３Ｄ顔の分析を実現するための基盤プロジェクトであり、最先端の技術を導入して顔の分析を実現します。
Networks of repeated neural modules with delayed neighbour coupling need stability guarantees for every number
Web platforms organize collective work, including content review and community maintenance, that imposes heter
Synthesizing a monocular video from a new camera trajectory requires preserving the observed scene geometry an
Can algorithms be learned and evolved as models, rather than repeatedly redesigned as programs? We explore thi
Digital marketplaces increasingly earn revenue from transaction commissions and seller-facing data services. S
The input space of single-spike neural networks decomposes into causal pieces, and the number of causal pieces
To facilitate the solving of complex problems, evolutionary multitask optimization is regarded as a promising
Indivisible resources allocated in advance may need to be reallocated when capacity reductions make existing a
Advanced persistent threats (APTs) are a major concern in federated learning (FL) deployments in critical sect
Solving imperfect-information games at scale rests on counterfactual regret minimization with the regret match
Face image quality assessment (FIQA) estimates the utility of a face image for automated face recognition and
Exploiting temporal information in datasets with high temporal dependencies (such as spoken keyword recognitio
Engineering design tools increasingly embed optimizers as ready-made components that users select by algorithm
The ability to represent temporal information is often hypothesized to underlie the efficiency and learning ca
Spiking neural networks (SNNs) have increasingly incorporated rich neuronal dynamics to enhance temporal proce
Pairwise comparison data are a standard supervision signal in preference learning, but disagreement in such da
In a repeated Stackelberg security game, a defender commits in every round to a randomized allocation of its r
We resolve the problem of unweighted online stochastic matching with a known arrival law by establishing its o
We prove that computing a complete contiguous $\varepsilon$-envy-free cake allocation is PPAD-complete for nor
We give new mechanisms for combinatorial auctions in the offline, secretary, and prophet-with-samples models.
We investigate the growth trajectory of online platforms operating as market makers in two-sided matching mark
We study the \emph{voter model with opinion graph}, a generalization of the standard (pull) voter model that a
Generating an image with a diffusion or flow-matching model typically involves integrating a velocity field fo
A fixed network of McCulloch-Pitts threshold units with weights in {-1,0,1} can hold other threshold networks
This work examines the transfer of a co-evolved communication mechanism between two robotic agents from a disc
Spiking neural networks (SNNs) offer sparse and event-driven computation, making them attractive for energy-co
Process-induced warpage, ceramic stress and solder strain limit the reliability of insulated-gate bipolar tran
Variational quantum algorithms turn choices of Hamiltonian, ansatz, and parameterization into a classical nonc
Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from
Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying
A reliable assessment of an optimizer robustness requires tracking controlled changes in parameters to identif
Open-pit mining operational planning involves allocating limited resources while satisfying production, equipm
A novel discovery is one which is both useful and surprising: a generative model's output is a useful discover
Fast and accurate qubit-state assignment is essential for feedback, calibration, and error correction in quant
Artificial intelligence increasingly serves as a natural-language interface to complex technical systems, lett
The Three-Dimensional Trailer Loading Problem (3D-TLP) involves determining the optimal placement and orientat
Connectome models of the fly nerve cord generate walking-like motor rhythms, but oscillation alone does not sh
Stochastic cell updates are often used throughout the life of a neural cellular automaton (NCA), from backprop