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HLXiON δ Ω Intent Σ Logic Ψ Synth Π Reason Γ Memory Processing: stat.ML
iON AI Synthesis
The search results for "stat.ML" showcase diverse applications of statistical machine learning in biological and computational sciences. For instance, graphical models like hidden Markov models enhance biological sequence analysis, while multifractal analysis reveals complex behaviors in human genome symbol sequences. Additionally, innovative approaches such as the Q-Drug framework and extreme value distribution methods optimize drug design and gene selection in microarray data analysis, respectively, demonstrating the wide-ranging impact of machine learning techniques in scientific research.
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arxiv.org
Parametric Inference for Biological Sequence Analysis

One of the major successes in computational biology has been the unification, using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied towards these problems include hidden Markov models for annotatio…

q-bio.GN cs.LG math.ST
arxiv.org
Multifractal information production of the human genome

We determine the Renyi entropies K_q of symbol sequences generated by human chromosomes. These exhibit nontrivial behaviour as a function of the scanning parameter q. In the thermodynamic formalism, there are phase transition-like phenomena close to the q=1 region. We develop a theoretical model for…

cond-mat.stat-mech nlin.CD physics.bio-ph q-bio.GN
arxiv.org
Q-Drug: a Framework to bring Drug Design into Quantum Space using Deep Learning

Optimizing the properties of molecules (materials or drugs) for stronger toughness, lower toxicity, or better bioavailability has been a long-standing challenge. In this context, we propose a molecular optimization framework called Q-Drug (Quantum-inspired optimization algorithm for Drugs) that leve…

quant-ph q-bio.MN q-bio.QM
arxiv.org
Extreme Value Distribution Based Gene Selection Criteria for Discriminant Microarray Data Analysis Using Logistic Regression

One important issue commonly encountered in the analysis of microarray data is to decide which and how many genes should be selected for further studies. For discriminant microarray data analyses based on statistical models, such as the logistic regression models, gene selection can be accomplished …

q-bio.QM q-bio.GN
arxiv.org
Long-range temporal correlation in Auditory Brainstem Responses to Spoken Syllable /da/

The speech auditory brainstem response (sABR) is an objective clinical tool to diagnose particular impairments along the auditory brainstem pathways. We explore the scaling behavior of the brainstem in response to synthetic /da/ stimuli using a proposed pipeline including Multifractal Detrended Movi…

q-bio.QM physics.bio-ph q-bio.NC
arxiv.org
Strong anomalous diffusion for free-ranging birds

Diffusion and anomalous diffusion are widely observed and used to study movement across organisms, resulting in extensive use of the mean and mean-squared displacement (MSD). However, these measures - corresponding to specific displacement moments - do not capture the full complexity of movement beh…

q-bio.PE cond-mat.stat-mech physics.bio-ph physics.data-an q-bio.QM
arxiv.org
Overlapping Probabilities of Top Ranking Gene Lists, Hypergeometric Distribution, and Stringency of Gene Selection Criterion

When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. This overlapping probability is well known to follow the hypergeometric distribution. Usually, the lengths of top-ranking gene …

q-bio.QM
arxiv.org
The Sustainability Gap in Robotics: A Large-Scale Survey of Sustainability Awareness in 50,000 Research Articles

We present a large-scale survey of sustainability communication and motivation in robotics research. Our analysis covers nearly 50,000 open-access papers from arXiv's cs.RO category published between 2015 and early 2026. In this study, we quantify how often papers mention social, ecological, and sus…

cs.RO cs.CY
arxiv.org
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions

Personal autonomous vehicles are cars, trucks and bikes capable of sensing their surrounding environment, planning their route, and driving with little or no involvement of human drivers. Despite the impressive technological achievements made by the industry in recent times and the hopeful announcem…

cs.CV cs.RO
arxiv.org
Identifying the Development and Application of Artificial Intelligence in Scientific Text

We describe a strategy for identifying the universe of research publications relevant to the application and development of artificial intelligence. The approach leverages the arXiv corpus of scientific preprints, in which authors choose subject tags for their papers from a set defined by editors. W…

cs.DL cs.IR