A rational knot or link can be put into a standard alternating format which has horizontal and vertical twist sites (double helices). The number and type of these twist sites are determined by terms of next-to-highest -degree in Kauffman's regular isotopy invariant . In particular, for a knot or link with $c…
On-device research index
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
169,291 papers · 148 categories
Trend · papers per month
48 results for “twist sites”
Alexander polynomial linked to twist sites in rational links.
problem Relating Alexander polynomial to twist sites in rational links.
method Using Kauffman's clock moves and a lattice for Alexander polynomial terms.
result Alexander polynomial value at (-1,0) determined by twist sites.
Site-specific recombination on supercoiled circular DNA molecules can yield a variety of knots and catenanes. Twist knots are some of the most common conformations of these products and they can act as substrates for further rounds of site-specific recombination. They are also one of the simplest families of knots and …
We show that if {L_n} is any infinite sequence of links with twist number tau(L_n) and with cyclotomic Jones polynomials of increasing span, then lim sup tau(L_n)=infty. This implies that any infinite sequence of prime alternating links with cyclotomic Jones polynomials must have unbounded hyperbolic volume. The main t…
We develop a model characterizing all possible knots and links arising from recombination starting with a twist knot substrate, extending previous work of Buck and Flapan. We show that all knot or link products fall into three well-understood families of knots and links, and prove that given a positive integer , the…
Learning to Infer Unobserved Behaviors: Estimating User's Preference for a Site over Other Sitescs.IR
Estimates users' preference for a site over others using engagement data.
problem Lack of data on users' interactions with other sites makes it hard to estimate preferences for a focal site.
method Uses Hierarchical Bayes Method with two estimation techniques: Markov Chain Monte Carlo and Stochastic Gradient with Langevin Dynamics.
result Good support found for the approach to computing personalized share of engagement.
Researchers explore non-coherent banding in site-specific recombination.
problem Understanding non-coherent banding in site-specific recombination.
method Survey of recent developments in non-coherent banding on knots.
result Recent advances in non-coherent banding model for site-specific recombination.
Learning Sequential Decisions from Multiple Sources via Group-Robust Markov Decision Processesstat.ME
Paper tackles robust decision-making from multiple sites with shared structure.
problem Learning robust sequential decisions from heterogeneous multi-site datasets.
method Group-Robust MDPs with d-rectangular uncertainty sets, feature-wise worst-case aggregation, and cluster-level pooling.
result Proves suboptimality bound for robust planning policy under robust partial coverage assumption.
RFMS optimizes model hyperparameters across remote sites for high-dimensional data.
problem Training machine learning models on remote data sites due to privacy and trust concerns.
method Bayesian Optimization for multi-objective hyperparameter tuning.
result Multi-objective Bayesian Optimization improves model performance across multiple data sites.
Clinical AI models fail to transfer between sites due to site-specific practices.
problem Clinical AI models perform poorly at new sites.
method Identify and isolate site-specific clinical practices affecting data distribution.
result A potential solution to improve model transferability.
A novel framework synthesizes treatment data across sites using optimal transport.
problem Estimating treatment effects across different sites with varying conditions.
method Distributional causal inference, Optimal Transport for alignment of control group distributions.
result Synthetic treatment group data aligns with true target distribution under general conditions.
Paper identifies key CpG methylation sites for breast cancer.
problem Early detection and treatment of breast cancer.
method Used machine learning on TCGA dataset to classify cancer vs. non-cancer samples.
result Reduced model with 25 key CpG sites achieves over 94% accuracy.
Meta-analysis improves personalized treatment rules across multiple sites.
problem Lack of generalizability in learning individualized treatment rules across different medical sites.
method Developed a method for individual-level meta-analysis of ITRs, borrowing sign-coherency information between sites.
result Jointly learned site-specific ITRs with improved generalizability.
Tree-based model averaging improves CATE estimation from diverse sites.
problem Limited sample size and privacy concerns prevent accurate personalized treatment effect estimation.
method Tree-based model averaging approach to estimate CATEs from multiple heterogeneous sites.
result Improved accuracy in estimating conditional average treatment effects (CATEs) across sites.
Study calculates site-specific Gordian distances between graph embeddings.
problem Determining the minimal number of crossing changes between graph embeddings.
method Covering space theory for proofs.
result Site-specific Gordian distances between Milnor links and trivial links are determined.
The study explores how different Grothendieck topologies and functors between categories preserve locality.
problem Exploring relationships between different Grothendieck topologies and functors.
method Using Grothendieck topologies and functors to relate categories and geometric objects.
result Objects like sheaves, groupoids, and functors are invariant under equivalences of Grothendieck topologies and certain functors.
Paper tackles online facility location with user requests and provides a quasi-linear time algorithm.
problem Online facility location problem with user requests and site selection costs.
method Design of a novel quasi-linear time algorithm based on the Hedge algorithm.
result Good theoretical guarantees on the performance of the novel algorithm.
Minimax Regret Estimation for Generalizing Heterogeneous Treatment Effects with Multisite Datastat.ME
Method improves robustness and generalizability of CATE estimation.
problem Lack of external validity in site-specific models for diverse populations.
method Minimax-regret framework with robust optimization.
result Interpretable closed-form solution for generalizable CATE model.
New federated method preserves privacy and estimates treatment effects.
problem Privacy-preserving causal inference for multi-site studies.
method Multiply robust nuisance function estimation, transfer learning.
result Efficient and optimal treatment effect estimation under different scenarios.
Owners of a web-site are often interested in analysis of groups of users of their site. Information on these groups can help optimizing the structure and contents of the site. In this paper we use an approach based on formal concepts for constructing taxonomies of user groups. For decreasing the huge amount of concepts…
Paper proves model structures equal for smooth manifolds and Cartesian spaces.
problem Equal model structures for differential geometry sites.
method Simple proof using local projective model structures.
result Plus construction suffices to sheafify presheaves.
FONT clusters patients across health systems with privacy and efficiency.
problem Challenges in multi-site cluster analysis due to data-sharing restrictions.
method Federated One-shot Ensemble Clustering (FONT) algorithm that requires only a single round of communication and exchanges only fitted model parameters and class labels.
result FONT improves consistency of patient clusters across sites compared to locally fitted clusters.
iDeepA predicts RNA-protein binding sites from RNA sequences using a CNN with attention.
problem Predicting RNA-protein binding sites from raw RNA sequences efficiently.
method Attention based convolutional neural network (iDeepA) encoding RNA sequences into one-hot encoding, followed by a CNN with an attention mechanism.
result iDeepA achieves comparable performance to state-of-the-art methods on CLIP-seq data.
Connectivity studies using resting-state functional magnetic resonance imaging are increasingly pooling data acquired at multiple sites. While this may allow investigators to speed up recruitment or increase sample size, multisite studies also potentially introduce systematic biases in connectivity measures across site…
The paper presents a test to determine when pooling datasets from multiple sites is beneficial for regression analysis.
problem Determining when pooling multi-site datasets improves regression analysis power.
method Developed a hypothesis test for classical and high-dimensional linear regression to assess when pooling datasets is sensible.
result Identified specific conditions under which pooling datasets improves power in regression analysis.
Desingularizes singular spaces using sheaves and groupoids.
problem Desingularizing singular spaces with complex structures.
method Axiomatization of Grothendieck sites, sheaves, and groupoids.
result Sheaves can encode candidate holonomy groupoids to desingularize spaces.
Memory Matching Networks classify DNA sequences for protein binding sites.
problem Manual construction of DNA motifs is difficult due to their complexity.
method Memory Matching Networks (MMN) learn a dynamic memory bank of encoded motifs and match them to new sequences.
result MMN effectively classifies DNA sequences as protein binding or nonbinding sites.
PLOT uses optimal transport to find neural site handles for causal abstraction.
problem Finding the relevant neural site for causal analysis is computationally challenging.
method PLOT employs optimal transport to localize causal variables from neural network outputs.
result PLOT efficiently finds intervention handles for causal abstraction in neural networks.
HBR improves normative modeling of neuroimaging data across multiple sites.
problem Dealing with nuisance variation in neuroimaging data across different sites.
method Hierarchical Bayesian regression (HBR) for multi-site normative modeling.
result HBR provides more accurate normative ranges compared to existing methods.
Develops theory of differential graded schemes for derived stacks.
problem Creating a theory for derived stacks using dg schemes.
method Formulates dg schemes as homotopy sites, equates to stacks on dg algebras.
result Infinity category of stacks represented by dg schemes is derived schemes.
Paper proposes federated offline RL for personalized medicine.
problem Privacy constraints and heterogeneity in healthcare data.
method Multi-site Markov decision process model and first federated policy optimization algorithm.
result The proposed algorithm achieves comparable suboptimality to centralized RL.
Study analyzes wind data from Greek islands to predict sea conditions.
problem Predicting sea conditions for refugee influx in Greece.
method Statistical analysis, ARMA models, cross-site correlation.
result ARMA(7,5) models predict average wind speed with RMSE < 1.9 km/h.
A cased-based reasoning method predicts rare events on strategic sites using satellite imagery.
problem Manual prediction of rare events on strategic sites is impractical due to large datasets.
method Case-based reasoning approach incorporating expert knowledge for irregular time series and small datasets.
result The method significantly outperforms random selection on challenging applications.
Unsupervised method detects surgical site infections from blood samples.
problem Detecting surgical site infections from blood samples without labeled data.
method Powerful kernels for multivariate time series with missing data handling.
result Framework shows superior performance compared to baselines.
Physics-informed GANs model subsurface flow at the Hanford Site.
problem Uncertainty quantification for subsurface flow modeling at the Hanford Site.
method Physics-informed GANs, hierarchical domain parallelism, multiple GPUs, efficient communication.
result Highly scalable physics-informed GANs model subsurface flow on Summit supercomputer.
Masked LARk prevents cross-site tracking while training models.
problem Cross-site tracking of user data through third-party cookies.
method Secure multi-party compute (MPC) protocol with masking.
result Prevents cross-site tracking and maintains model training flexibility.
Study of surface defects in gauge theories leads to duality and separation of variables.
problem Understanding surface observables and their transitions in gauge theories.
method Utilized Fourier transformations and spectral problems to derive dualities and separation of variables.
result Exact duality between spectral problems of spin chains and Gaudin models.
New biomarkers for autism detected from R-fMRI data.
problem Challenges in extracting functional biomarkers from multi-site R-fMRI data for complex neuropsychiatric disorders.
method Developed pipelines to extract participant-specific connectomes from functionally-defined brain areas, compared across participants, and predicted neuropsychiatric status.
result 67% prediction accuracy on ABIDE dataset, significantly better than previous results.
Computational approaches to transcription factor binding site identification have been actively researched for the past decade. Negative examples have long been utilized in de novo motif discovery and have been shown useful in transcription factor binding site search as well. However, understanding of the roles of nega…
New method corrects MRI biases across scanners and sites.
problem Site and scanner biases in diffusion MRI data.
method Learning invariant representations using variational auto-encoders (VAE).
result Improvements on test data relative to a baseline method.
GOPSA optimizes EEG data for cross-site age prediction, improving performance on multiple metrics.
problem Predictive shifts in EEG data from different sites and participants.
method Geodesic Optimization for Predictive Shift Adaptation (GOPSA) on the SPD manifold.
result Significantly higher performance on age prediction metrics compared to state-of-the-art methods.
Algorithm detects surgical site infections from hospital data.
problem Reduces incidence of surgical site infections in hospitals.
method Machine learning algorithms trained on hospital data.
result Identifies all SSIs with minimal false positives.
DWC consolidates neural networks trained on separate datasets, improving performance.
problem Training deep neural networks on large, distributed datasets is challenging.
method DWC: a continual learning method to consolidate weights of separate neural networks trained on independent datasets.
result DWC led to increased performance on test sets from different sites compared to an ensemble baseline.
We develop a topological model of site-specific recombination that applies to substrates which are the connected sum of two torus links of the form . Then we use our model to prove that all knots and links that can be produced by site-specific recombination on such substrates are contained in one of two…
Modeling infection hotspots to quantify effects of contact tracing and testing.
problem Capturing the role of infection hotspots in disease transmission.
method Temporal point process modeling framework to represent visits and disease transmission.
result Estimation of transmission rates at sites and households using Bayesian optimization.
Bayesian models forecast COVID-19 hospitalizations at single sites.
problem Forecasting daily COVID-19 hospitalizations at a single hospital.
method Hierarchical Bayesian models with generalized Poisson likelihood and autoregressive/Gaussian process latent processes.
result Demonstrated superior performance compared to baselines in public datasets.
New method detects RNA modifications without prior training, revealing novel sites.
problem Detecting RNA modifications with high accuracy and sensitivity.
method Anomaly detection using nanopore raw ionic current signals and nearest neighbor comparison.
result Detects diverse RNA modifications without prior training, including a novel 2'-O-methylated site in DENV.
Associate stacks to Poisson manifolds for equivalence checking.
problem Equivalence checking of Poisson manifolds.
method Associate stacks to Poisson manifolds using Dirac manifolds and closed 2-forms.
result Two Poisson manifolds are equivalent if their associated stacks are isomorphic.