Tag: process
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The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor
The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor Cursor is great at writing code but not as good when it comes to design The post The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor appeared first on Towards Data Science. Soner Yıldırım Go to…
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MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series
MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series arXiv:2509.19577v1 Announce Type: new Abstract: Time series analysis has emerged as an important tool for improving patient diagnosis and management in healthcare applications. However, these applications commonly face two critical challenges: time misalignment and data sparsity. Traditional approaches address these issues through…
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On Experiments
On Experiments arXiv:2508.08288v1 Announce Type: new Abstract: The scientific process is a means for turning the results of experiments into knowledge about the world in which we live. Much research effort has been directed toward automating this process. To do this, one needs to formulate the scientific process in a precise mathematical language. This paper…
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Determination of Particle-Size Distributions from Light-Scattering Measurement Using Constrained Gaussian Process Regression
Determination of Particle-Size Distributions from Light-Scattering Measurement Using Constrained Gaussian Process Regression arXiv:2507.03736v1 Announce Type: new Abstract: In this work, we propose a novel methodology for robustly estimating particle size distributions from optical scattering measurements using constrained Gaussian process regression. The estimation of particle size distributions is commonly formulated as a Fredholm integral equation of…
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Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics
Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics arXiv:2506.20935v1 Announce Type: new Abstract: Forecasting geopolitical conflict from data sources like the Global Database of Events, Language, and Tone (GDELT) is a critical challenge for national security. The inherent sparsity, burstiness,…
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Attaining LLM Certainty with AI Decision Circuits
Attaining LLM Certainty with AI Decision Circuits The promise of AI agents has taken the world by storm. Agents can interact with the world around them, write articles (not this one though), take actions on your behalf, and generally make the difficult part of automating any task easy and approachable. Agents take aim at the most…
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Beyond the Code: Unconventional Lessons from Empathetic Interviewing
Beyond the Code: Unconventional Lessons from Empathetic Interviewing Recently, I’ve been interviewing Computer Science students applying for data science and engineering internships with a 4-day turnaround from CV vetting to final decisions. With a small local office of 10 and no in-house HR, hiring managers handle the entire process. This article reflects on the lessons…
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Rolled Gaussian process models for curves on manifolds
Rolled Gaussian process models for curves on manifolds arXiv:2503.21980v1 Announce Type: cross Abstract: Given a planar curve, imagine rolling a sphere along that curve without slipping or twisting, and by this means tracing out a curve on the sphere. It is well known that such a rolling operation induces a local isometry between the sphere…
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Discrete Markov Probabilistic Models
Discrete Markov Probabilistic Models arXiv:2502.07939v1 Announce Type: new Abstract: This paper introduces the Discrete Markov Probabilistic Model (DMPM), a novel algorithm for discrete data generation. The algorithm operates in the space of bits ${0,1}^d$, where the noising process is a continuous-time Markov chain that can be sampled exactly via a Poissonian clock that flips labels…
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Understanding Deduplication Methods: Ways to Preserve the Integrity of Your Data
Understanding Deduplication Methods: Ways to Preserve the Integrity of Your Data Increasing growth and data complexities have made data deduplication even more relevant Data duplication is still a problem for many organisations. Although data processing and storage systems have developed rapidly along with technological advances, the complexity of the data produced is also increasing. Moreover, with…
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A Generalized Unified Skew-Normal Process with Neural Bayes Inference
A Generalized Unified Skew-Normal Process with Neural Bayes Inference arXiv:2411.17400v1 Announce Type: new Abstract: In recent decades, statisticians have been increasingly encountering spatial data that exhibit non-Gaussian behaviors such as asymmetry and heavy-tailedness. As a result, the assumptions of symmetry and fixed tail weight in Gaussian processes have become restrictive and may fail to capture…