Pattern recognition identifies Giant Radio Sources from NVSS catalog.
problem Identifying Giant Radio Sources (GRS) from NVSS catalog data.
method Applied pattern recognition techniques, specifically decision-tree software, to NVSS catalog source pairs.
result 97.8% accuracy in correctly ranking GRS and non-GRS pairs.
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification.…
New model constructs astronomical catalogs from images efficiently.
problem Building accurate catalogs from large image datasets.
method Generative model with MCMC and VI for inference.
result Variational inference is 1000x faster with similar accuracy.
We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks, a probabilistic graphical model, that allows us to perform inference to pre- dict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incom…
The study uses historical revenue data to forecast music catalog cashflows and multipliers.
problem Valuation of music catalogs based on historical revenue data.
method Risk-neutral approach using discounted cashflows formula.
result Ask prices are close to multipliers justified by median song cashflows, while best bids are near multipliers justified by bottom decile cashflows.
Celeste learns astronomical catalogs from large datasets.
problem Inferring astronomical catalogs from large-scale datasets.
method Scalable Bayesian inference with Julia, parallel optimization.
result Learned catalogs from modern large-scale astronomical datasets.
New method speeds up uncertainty estimation for large datasets in causal inference.
problem Computational infeasibility of bootstrap-based uncertainty quantification for large datasets.
method Extends cBLB algorithm to kernel methods, combining subsampling and resampling.
result Achieves computational scalability with nominal coverage.
CHARM creates mock halo catalogs from dark matter density fields using neural networks.
problem Creating accurate mock halo catalogs for cosmological studies is computationally expensive.
method CHARM uses multi-stage neural spline flow networks to learn the mapping from dark matter density fields to halo catalogs.
result Mock halo catalogs have the same statistical properties as those from high-resolution N-body simulations.
Machine learning detects type Ia supernovae from photometric data.
problem Detecting type Ia supernovae accurately from photometric data.
method Machine learning approach using only real observation data.
result Good results on real data from the Open Supernovae Catalog.
BLISS detects and separates astronomical sources quickly and accurately.
problem Detecting and separating overlapping astronomical sources in large images.
method Bayesian Light Source Separator (BLISS) using deep generative models and variational inference.
result BLISS can process megapixel images in seconds and produce highly accurate catalogs.
RecoBERT uses a language model to recommend items from catalogs.
problem Harnessing language models for text-based item recommendations.
method RecoBERT is a BERT-based approach that learns specialized language models for item recommendations without requiring labeled data.
result RecoBERT outperforms other techniques in inferring item similarities from textual catalogs.
EQShapelets detect earthquakes with high accuracy and interpretability.
problem Automated detection and cataloging of earthquakes.
method Time-series shape-based approach embedded in machine learning.
result EQShapelets detected all cataloged and 281 uncataloged events with lower false detection rate.
AI classifies tourist events for better service.
problem Classifying tourist events efficiently across diverse sources.
method CRISP-DM, supervised machine learning, NLP.
result Automatic classification tool for consistent event catalogs.
Machine learning separates Gaia DR2 stars into accreted and in-situ categories.
problem Identifying accreted stars from Gaia DR2 data using limited 5D kinematics.
method Transfer learning on mock Gaia catalogs, then cross-matched with real data.
result Identifies 767,000 accreted stars within Gaia DR2.
We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy c…
Analog methods improve forecast accuracy in complex models.
problem Improving forecast accuracy in complex models like Lorenz-96.
method Constructing analogs using variational autoencoders for ensemble data assimilation.
result Constructed analogs perform as well as a full ensemble square root filter.
The paper evaluates the probability distributions of analog-to-target distances for multiple analogs.
problem Understanding the performance of analog applications through the distribution of distances to target states.
method Theoretical analysis and numerical experiments using dynamical systems theory.
result The size of the catalog and dimensionality affect the probability distributions of the K-best analogs.
Bayesian method finds voids in galaxy surveys with deep neural networks.
problem Finding genuine matter underdensities in sparse galaxy surveys is underconstrained.
method Deep graph neural network evolves 'test particles' to sample from stochastic void definitions.
result Trained model performs well and finds Bayes-optimal void mappings.
System solves author name ambiguity in e-commerce catalogs.
problem Finding correct author names in e-commerce catalogs with abbreviations and spelling variants.
method Composite system using open data sources and machine learning techniques for natural language processing.
result Top proposal of the system is the normalized author name with 72% accuracy.
Method retrieves similar fashion items from images and text, enabling style refinement.
problem Lack of intuitive, interactive refinement in search engines for fashion items.
method Joint visual-textual embedding training, Mini-Batch Match Retrieval, attribute extraction.
result Improved performance in multimodal style search, demonstrated through benchmark.
Kolmogorov-Arnold network improves GW catalog posterior construction.
problem Efficiently constructing posterior distributions for GW catalogs.
method Using the Kolmogorov-Arnold network to create lightweight neural density estimators.
result Kolmogorov-Arnold network achieves superior interpretability and accuracy in posterior construction.
System optimizes product images for e-commerce, enhancing customer engagement.
problem Optimizing product images for e-commerce to improve customer engagement.
method Machine learning, deep learning, and computer vision techniques applied to large e-commerce catalogs.
result System produces superior image sets tailored to customer preferences.
TUV Austria proposes certification for ML applications to ensure reliability.
problem Ensuring trust in AI applications to meet societal reliance requirements.
method Holistic approach analyzing security, functionality, data quality, ethics, and criticality levels.
result Certification process for low-risk ML applications in supervised learning.
We consider the "intrinsic" symmetry group of a two-component link L, defined to be the image Σ(L) of the natural homomorphism from the standard symmetry group $\MCG(S^3,L)$ to the product $\MCG(S^3) \cross \MCG(L)$. This group, first defined by Whitten in 1969, records directly whether L is isotopic to a link $L…
This paper introduces two-dimensional diagrams that are slight generalizations of moment map images for toric four-manifolds and catalogs techniques for reading topological and symplectic properties of a symplectic four-manifold from these diagrams. The paper offers a purely topological approach to toric manifolds as w…
Automatically identifies RRLyrae stars from VVV survey data.
problem Classifying RRLyrae stars from a large dataset of light curves.
method Developed an automatic ML-based procedure to identify RRLs, using features like period and intensity, and pseudo-colors.
result Constructed an ensemble classifier with Recall of 0.48 and Precision of 0.86 over 15 tiles.
Paper determines 2-adjacent knots up to 12 crossings.
problem Identifying 2-adjacent knots with up to 12 crossings.
method Used Heegaard Floer d-invariants and Alexander polynomial to obstruct 2-adjacency.
result Proved conjectures about 2-adjacent knots by Ito and Kato.
Improved cover detection in music datasets with novel triplet loss.
problem Challenging task of automatically detecting covers in audio datasets.
method Convolutional neural network mapping melodic features to embeddings, training to minimize cover distance and maximize non-cover distance.
result New prototypical triplet loss improves accuracy for large datasets and live songs.
Paper tackles circularity issues in machine learning predictions.
problem Circularity problems in machine learning predictions.
method Not specified in the abstract.
result Not specified in the abstract.
Taxonomy for ML in simulations, covering patterns and algorithms.
problem Enhancing simulations using machine learning.
method Presentation of eight patterns and three algorithmic areas.
result Catalog of activities and patterns for ML integration in simulations.
In this paper, we work to construct mosaic representations of knots on the torus, rather than in the plane. This consists of a particular choice of the ambient group, as well as different definitions of contiguous and suitably connected. We present conditions under which mosaic numbers might decrease by this projection…
ASKAP observes a region of the Galactic plane, identifying 3963 radio sources.
problem Characterizing radio sources in the Galactic plane using ASKAP observations.
method 912 MHz observations with 15 ASKAP antennas, source characterization using CAESAR.
result Differential source counts in agreement with previous surveys, spectral index estimation for sources.
Identifies LA-groups via VB-group structure and complementary actions.
problem Understanding the structure and integrability of LA-groups.
method Identifies LA-groups via VB-group structure and complementary actions up to homotopy.
result Establishes an equivalence between LA-groups and LA-matched pairs.
Deep learning classifies galaxies from Dark Energy Survey in just 8 minutes.
problem Classifying galaxies from large-scale surveys.
method Transfer learning from pre-trained neural networks.
result Achieved state-of-the-art accuracy of 99.6% in galaxy classification.
Elliptic curve governs Hopf linking in symmetric tensegrity.
problem Understanding Hopf linking in A4-symmetric tensegrity.
method Parametrized by points on the elliptic curve 30a2.
result Only one rational point corresponds to a stable configuration.
CHAMELEON uses RNNs to recommend news sequences better than other methods.
problem Improving news recommendation accuracy and catalog coverage.
method Hybrid meta-architecture CHAMELEON with RNNs for sequence modeling and side information.
result Significantly higher recommendation accuracy and catalog coverage.
The paper tackles robust design selection for online experiments under uncertain interference mechanisms.
problem Designing experiments in ads, recommendations, and member-experience systems when interference mechanisms are unknown.
method Formulates the problem as robust design selection over uncertain exposure mechanisms. Compares designs by worst-case planning risk over an ambiguity set combining various factors.
result Develops a geometry-aware guarantee and robust selector theorem with excess-risk control, exact recovery under separation, and certified shortlists when the risk surface is flat.
PhaseLink uses deep learning to accurately link seismic phases.
problem Linking seismic phases from different sensors, especially in overlapping events.
method Deep learning framework trained on synthetic seismic data.
result PhaseLink can associate P- and S-picks separated by ~12 seconds.
Develops a support-aware framework for reserve-policy selection in advertising markets.
problem Log-based reserve-price evaluation risks weak support and subgroup harm.
method Support-aware offline decision framework converting logged evidence into certified policies.
result Preserves the best gate-passing policy while eliminating only policies with certified regret.
OpenTag extracts missing attribute values from product descriptions.
problem Extract missing attribute values from product descriptions.
method Developed a deep tagging model OpenTag using LSTM and CRF, with an attention mechanism and active learning.
result OpenTag discovers new attribute values with minimal human annotation, achieving high F-score.
Similar to knots in S^3, any knot in a lens space has a grid diagram from which one can combinatorially compute all of its knot Floer homology invariants. We give an explicit description of the generators, differentials, and rational Maslov and Alexander gradings in terms of combinatorial data on the grid diagram. Moti…
Experimentally identified 22 L-space knots with tunnel number >1, some having high genus and braid index.
problem Identifying L-space knots with tunnel number greater than 1.
method Cataloging hyperbolic manifolds, using SnapPy and KLO to find knot presentations as closures of positive braids.
result Found 9 asymmetric L-space knot complements with tunnel number 2, and 22 with tunnel number 1.
Method finds reference products for a given item.
problem Finding relevant products for a given item.
method Product representation learning and fingerprint-type vector searching.
result The method outperforms peer services in search return rate and precision.
PICZL improves photometric redshifts for AGN in all-sky surveys.
problem Challenges in accurately computing photo-z for AGN due to interplay of SMBH and host galaxy emissions.
method PICZL uses an ensemble of CNNs with cross-channel integration of image and catalog data, leveraging Gaussian mixture models.
result PICZL achieves a photo-z variance of 4.5% and outlier fraction of 5.6% on a validation sample of 8098 AGN, outperforming previous methods.
We study singularities of algebraic curves associated with 3d N=2 theories that have at least one global flavor symmetry. Of particular interest is a class of theories T_K labeled by knots, whose partition functions package Poincare polynomials of the S^r-colored HOMFLY homologies. We derive the defining equation, call…
New methods speed up fitting for large datasets with noisy observations.
problem Fitting large datasets with Gaussian noise and known covariance.
method Two minibatch variants of extreme deconvolution, online EM algorithm, and gradient-based optimisation.
result Methods can scale to larger models and fit larger datasets faster.
Deep learning's success requires vast computing power, making future progress unsustainable.
problem Deep learning's success is heavily dependent on computing power, making future progress unsustainable.
method Cataloging and extrapolating the dependency on computing power for various deep learning applications.
result Continued progress in deep learning applications will require more computationally-efficient methods.
The paper confirms two groups of gamma-ray bursts using a new nonparametric metric.
problem Determining the number of inherent groups in gamma-ray bursts.
method A new nonparametric interpoint distance-based measure, combined with clustering methods.
result Confirms two groups of short and long gamma-ray bursts.