22 papers · ranked by Valyu relevance
Aanya Pratapneni, Alice Yuan, TJ Tsai
Recent works have explored ways to handle uncertainty in dynamic time warping (DTW) alignment paths through the use of differentiable variants of DTW like Soft-DTW. In this paper, we approach the issue of uncertainty in DTW alignment paths in a different way. Given a DTW alignment path, we propose a metric that…
Pelin Icer Baykal, Mike Simonov, Dhrithi Deshpande, Ful Belin Korukoglu + 8 more
Genomic research relies on accurate and reproducible computational analyses of DNA sequencing data to draw reliable biological conclusions. Read mapping, the process of aligning reads to a reference genome, is central to many applications, including variant detection and comparative genomics. While several tools have…
Yue Guo, Yi Yang
Large language models (LLMs) are now rapidly advancing and surpassing human abilities on many natural language tasks. However, aligning these super-human LLMs with human knowledge remains challenging because the supervision signals from human annotators may be wrong. This issue, known as the "superalignment" problem…
Authors not listed
In molecular machine learning, the choice of the representation of molecules can have a significant impact on model performance. However, understanding the root causes of these performance differences often proves challenging. One promising approach to explore model behavior is representational alignment, which…
James H. Collier, Lloyd Allison, Arthur M. Lesk, Peter J. Stuckey + 2 more
Structural molecular biology depends crucially on computational techniques that compare protein three-dimensional structures and generate structural alignments (the assignment of one-to-one correspondences between subsets of amino acids based on atomic coordinates.) Despite its importance, the structural alignment…
Zijie Qiu, Sheng Xu, Junkang Wei, Tao Shen + 1 more
Understanding the three-dimensional structure of RNA is crucial for studying various biological processes. Accurate alignment and comparison of RNA structures are essential for illustrating RNA functionality and evolution. The existing RNA alignment tools suffer from limitations such as size-dependency of scoring…
Martin C. Frith
Sequence alignment remains fundamental in bioinformatics. Pairwise alignment is traditionally based on ad hoc scores for substitutions, insertions, and deletions, but can also be based on probability models (pair hidden Markov models: PHMMs). PHMMs enable us to: fit the parameters to each kind of data, calculate the…
Yutong Duan, J. Silber, T. Claybaugh, S. P. Ahlen + 2 more
'G. Tarlé'] The Dark Energy Spectroscopic Instrument (DESI) is under construction to measure the expansion history of the universe using the Baryon Acoustic Oscillation (BAO) technique. The spectra of 35 million galaxies and quasars spanning over 14000 deg2 will be measured during the life of the experiment. A new…
Jürgen Behr, Timm Michel, Maya Giridhar, Santra Santhosh + 11 more
Large- to ultra-large-scale synthesis of nucleic acids is becoming an increasingly important tool for understanding and manipulating biological systems, as well as for developing new technologies based on engineered biological materials, including DNA-based nanofabrication, aptamers and writing digital data at the…
Chiwei Zhu, Benfeng Xu, Quan Wang, Yongdong Zhang + 1 more
As large language models attract increasing attention and find widespread application, concurrent challenges of reliability also arise at the same time. Confidence calibration, an effective analysis method for gauging the reliability of deep models, serves as a crucial tool for assessing and improving their…
Granville J. Matheson, Andrew Gray
Neuroimaging, in addition to many other fields of clinical research, is both time-consuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is exacerbated by the use of…
Granville J. Matheson
Positron emission tomography (PET), along with many other fields of clinical research, is both timeconsuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is…
Basinepalli Kothireddy Gari Diwakarreddy, S Abishek, Amal Andrews, Lenny Vasanthan + 1 more
Range of motion (ROM) serves as a crucial metric for assessing movement impairments. Traditionally, clinicians use goniometers to measure the ROM, but this method relies on the clinician’s skill, in particular for difficult joints such as the shoulder and neck joints. Recent studies have explored the use of wearable…
Attila Krajcsi
In the behavioral sciences, robust phenomena having large effect sizes and related statistical power may be unreliable. This relation is in contrast to the view that both statistical power and reliability depend similarly on measurement error. In this view, robust but unreliable phenomena can be considered as a…
Aleksandra Królikowska, Paweł Reichert, Jon Karlsson, Caroline Mouton + 2 more
'Caroline Mouton' 'Roland Becker' 'Robert Prill'] A large space still exists for improving the measurements used in orthopaedics and sports medicine, especially as we face rapid technological progress in devices used for diagnostic or patient monitoring purposes. For a specific measure to be valuable and applicable in…
Authors not listed
The Protein Data Bank (PDB) is one of the richest open‑source repositories in biology, housing over 277,000 macromolecular structural models alongside much of the experimental data that underpins these models. By systematically collecting, validating, and indexing these models, the PDB has accelerated structural…
Yiling Chen, Shi Feng, Paul Kattuman, Fang-Yi Yu
How can we assess the reliability of a dataset without access to ground truth? We introduce the problem of reliability scoring for datasets collected from potentially strategic sources. The true data are unobserved, but we see outcomes of an unknown statistical experiment that depends on them. To benchmark reliability…
Sanjay M. Joshi
Reliability is probability of success in a success-failure experiment. Confidence in reliability estimate improves with increasing number of samples. Assurance sets confidence level same as reliability to create one number for easier communication. Assuming binomial distribution for the samples, closedform expression…
Rafdzah Zaki, Awang Bulgiba, Noorhaire Nordin, Noor Azina Ismail
Objective(s): Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used…
Sébastien Buczinski, Paul Mills
Simple Summary Veterinary science is based on data collection at the animal or herd level. Beyond the variability in the variable in question, the data collected can depend on the device used or the person performing the measurement. Determination of these sources of variation is crucial to be able to use these…
Sercan Kahveci, Arne C. Bathke, Jens Blechert
While it has become standard practice to report the reliability of self-report scales, it remains uncommon to do the same for experimental paradigms. To facilitate this practice, we review old and new ways to compute reliability in reaction-time tasks, and we compare their accuracy using a simulation study. Highly…
Authors not listed
Machine learning (ML) models are increasingly used in quantum chemistry, but their reliability hinges on uncertainty quantification (UQ). In this study, we compare two prominent UQ paradigms—Deep Evidential Regression (DER) and Deep Ensembles—on the QM9 and WS22 datasets, with a specific emphasis on the role of post…