Data Science

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

Scientists uncover new method to generate protein datasets for training AI

6 Months Using AI for Actual Work: What's Incredible, What's Overhyped, and What's Quietly Dangerous

Six months ago I committed to using AI tools for everything I possibly could in my work. Every day, every task, every workflow. Here's th...

[2602.12933] Deep-Learning Atlas Registration for Melanoma Brain Metastases: Preserving Pathology While Enabling Cohort-Level Analyses

This article presents a deep-learning framework for registering melanoma brain metastases (MBM) to a common atlas, enhancing cohort-level...

[2602.12919] EPRBench: A High-Quality Benchmark Dataset for Event Stream Based Visual Place Recognition

EPRBench introduces a benchmark dataset for event stream-based visual place recognition, addressing challenges in low-light and high-spee...

[2602.12917] Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment

This article presents a novel ultrasound-guided method for real-time 3D visualization of spinal motion to assess spinal instability, aimi...

[2602.12869] X-VORTEX: Spatio-Temporal Contrastive Learning for Wake Vortex Trajectory Forecasting

The paper presents X-VORTEX, a novel spatio-temporal contrastive learning framework designed to enhance wake vortex trajectory forecastin...

[2602.12833] TRACE: Temporal Reasoning via Agentic Context Evolution for Streaming Electronic Health Records (EHRs)

TRACE introduces a novel framework for temporal reasoning in electronic health records, enhancing prediction accuracy and clinical safety...

[2602.12828] GRAIL: Geometry-Aware Retrieval-Augmented Inference with LLMs over Hyperbolic Representations of Patient Trajectories

The GRAIL framework enhances next-visit event prediction in healthcare by utilizing geometry-aware retrieval and hyperbolic representatio...

[2602.12798] Can Neural Networks Provide Latent Embeddings for Telemetry-Aware Greedy Routing?

The paper explores a novel algorithm, Placer, which utilizes Message Passing Networks to create latent embeddings for telemetry-aware gre...

[2602.12783] SQuTR: A Robustness Benchmark for Spoken Query to Text Retrieval under Acoustic Noise

The paper introduces SQuTR, a new benchmark for evaluating the robustness of spoken query retrieval systems under various acoustic noise ...

[2602.12687] Trust the uncertain teacher: distilling dark knowledge via calibrated uncertainty

This paper introduces Calibrated Uncertainty Distillation (CUD), a novel approach to knowledge distillation that enhances the transfer of...

[2602.12659] IndicFairFace: Balanced Indian Face Dataset for Auditing and Mitigating Geographical Bias in Vision-Language Models

The paper introduces IndicFairFace, a balanced dataset aimed at addressing geographical bias in Vision-Language Models (VLMs) by represen...

[2602.12656] PMG: Parameterized Motion Generator for Human-like Locomotion Control

The PMG paper presents a novel Parameterized Motion Generator for humanoid locomotion, addressing challenges in adapting motion tracking ...

[2602.12635] Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats

This article evaluates HiFloat formats for low-bit inference on Ascend NPUs, highlighting their efficiency and compatibility with state-o...

[2602.12593] RQ-GMM: Residual Quantized Gaussian Mixture Model for Multimodal Semantic Discretization in CTR Prediction

The paper introduces RQ-GMM, a novel model for improving click-through rate (CTR) prediction by effectively discretizing multimodal embed...

[2602.12592] Power Interpretable Causal ODE Networks: A Unified Model for Explainable Anomaly Detection and Root Cause Analysis in Power Systems

The paper presents Power Interpretable Causal ODE Networks (PICODE), a novel model for explainable anomaly detection and root cause analy...

[2602.12574] Monte Carlo Tree Search with Reasoning Path Refinement for Small Language Models in Conversational Text-to-NoSQL

This paper presents a novel framework, Stage-MCTS, which enhances small language models' ability to generate NoSQL queries through conver...

[2602.12547] A consequence of failed sequential learning: A computational account of developmental amnesia

This article presents a computational model addressing developmental amnesia, characterized by impaired episodic memory and intact semant...

[2602.12517] Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games

The paper presents Bench-MFG, a benchmark suite designed to standardize evaluations in learning for stationary Mean Field Games, addressi...

[2602.12542] Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference

The paper presents ExtraCare, a novel domain adaptation method for predictive healthcare that enhances accuracy and transparency by decom...

[2602.12484] A Lightweight and Explainable DenseNet-121 Framework for Grape Leaf Disease Classification

This article presents a novel DenseNet-121 framework for classifying grape leaf diseases, achieving high accuracy and interpretability wh...

[2602.12413] Soft Contamination Means Benchmarks Test Shallow Generalization

This paper explores how soft contamination in training data affects the evaluation of large language models (LLMs) on benchmarks, reveali...