Papers Sand
“Sand” 태그가 달린 논문 107편 · 필터 해제
Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound
Deep reinforcement learning (DRL) agents excel in solving complex decision-making tasks across various domains. However, they often require a substantial number of training steps and a vast experience replay buffer, lead…
counterfactualDecision MakingDeep Reinforcement LearningMuJoCo+1SAND: Boosting LLM Agents with Self-Taught Action Deliberation
Large Language Model (LLM) agents are commonly tuned with supervised finetuning on ReAct-style expert trajectories or preference optimization over pairwise rollouts. Most of these methods focus on imitating specific expe…
Large Language ModelSandDRIVE Through the Unpredictability:From a Protocol Investigating Slip to a Metric Estimating Command Uncertainty
Off-road autonomous navigation is a challenging task as it is mainly dependent on the accuracy of the motion model. Motion model performances are limited by their ability to predict the interaction between the terrain an…
Autonomous NavigationSandWonderPlay: Dynamic 3D Scene Generation from a Single Image and Actions
WonderPlay is a novel framework integrating physics simulation with video generation for generating action-conditioned dynamic 3D scenes from a single image. While prior works are restricted to rigid body or simple elast…
SandScene GenerationVideo GenerationUniPhy: Learning a Unified Constitutive Model for Inverse Physics Simulation
We propose UniPhy, a common latent-conditioned neural constitutive model that can encode the physical properties of diverse materials. At inference UniPhy allows `inverse simulation' i.e. inferring material properties by…
SandSAND: One-Shot Feature Selection with Additive Noise Distortion
Feature selection is a critical step in data-driven applications, reducing input dimensionality to enhance learning accuracy, computational efficiency, and interpretability. Existing state-of-the-art methods often requir…
Computational Efficiencyfeature selectionSandReal-time Pollutant Identification through Optical PM Micro-Sensor
Air pollution remains one of the most pressing environmental challenges of the modern era, significantly impacting human health, ecosystems, and climate. While traditional air quality monitoring systems provide critical …
SandSeeing A 3D World in A Grain of Sand
We present a snapshot imaging technique for recovering 3D surrounding views of miniature scenes. Due to their intricacy, miniature scenes with objects sized in millimeters are difficult to reconstruct, yet miniatures are…
3DGS3D ReconstructionNovel View SynthesisSandToward a Flexible Framework for Linear Representation Hypothesis Using Maximum Likelihood Estimation
Linear representation hypothesis posits that high-level concepts are encoded as linear directions in the representation spaces of LLMs. Park et al. (2024) formalize this notion by unifying multiple interpretations of lin…
counterfactualSandA recursive Bayesian neural network for constitutive modeling of sands under monotonic loading
In geotechnical engineering, constitutive models play a crucial role in describing soil behavior under varying loading conditions. Data-driven deep learning (DL) models offer a promising alternative for developing predic…
Bayesian InferenceSandUncertainty QuantificationVariational InferenceAn Interpretable ML-based Model for Predicting p-y Curves of Monopile Foundations in Sand
Predicting the lateral pile response is challenging due to the complexity of pile-soil interactions. Machine learning (ML) techniques have gained considerable attention for their effectiveness in non-linear analysis and …
SandHow Well Did U.S. Rail and Intermodal Freight Respond to the COVID-19 Pandemic vs. the Great Recession?
This paper analyzes and compares patterns of U.S. domestic rail freight volumes during, and after the disruptions caused by the 2007-2009 Great Recession and the COVID-19 pandemic in 2020. Trends in rail and intermodal s…
SandEPi-cKANs: Elasto-Plasticity Informed Kolmogorov-Arnold Networks Using Chebyshev Polynomials
Multilayer perceptron (MLP) networks are predominantly used to develop data-driven constitutive models for granular materials. They offer a compelling alternative to traditional physics-based constitutive models in predi…
Kolmogorov-Arnold NetworksSandIntegrating systematic surveys with historical data to model the distribution of Ornithodoros turicata americanus, a vector of epidemiological concern in North America
Globally, vector-borne diseases are increasing in distribution and frequency, affecting humans, domestic animals and livestock, and wildlife. Science-based management and prevention of these diseases requires a sound und…
SandSensitivityOn Vision Transformers for Classification Tasks in Side-Scan Sonar Imagery
Side-scan sonar (SSS) imagery presents unique challenges in the classification of man-made objects on the seafloor due to the complex and varied underwater environments. Historically, experts have manually interpreted SS…
Binary ClassificationClassificationComputational EfficiencySand+1Compatibility studies of loquat scions with loquat and quince rootstocks
Experiment 1. Rooting of quince hardwood cuttings: Rooting success was influenced by both the concentrations of IBA and the selection of rooting media. However, the control group (without IBA) notably enhanced rooting wh…
SandComputer-Generated Sand Mixtures and Sand-based Images
This paper aims to verify the effectiveness of the software implementation of the proposed algorithm in creating computer-generated images of sand mixtures using a photograph of sand as an input and its effectiveness in …
SandSharkTrack: an accurate, generalisable software for streamlining shark and ray underwater video analysis
Elasmobranchs (shark sand rays) represent a critical component of marine ecosystems. Yet, they are experiencing global population declines and effective monitoring of populations is essential to their protection. Underwa…
Multi-Object TrackingObject TrackingSandReduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs
We propose accelerating the simulation of Lagrangian dynamics, such as fluid flows, granular flows, and elastoplasticity, with neural-operator-based reduced-order modeling. While full-order approaches simulate the physic…
Elasticity3DGoop2DMultiMaterial2DPlasticine3D+5Accurate and fast anomaly detection in industrial processes and IoT environments
We present a novel, simple and widely applicable semi-supervised procedure for anomaly detection in industrial and IoT environments, SAnD (Simple Anomaly Detection). SAnD comprises 5 steps, each leveraging well-known sta…
Anomaly DetectionFeature ImportanceSand