This paper introduces a new approach for the automated reconstruction - reassembly of fragmented objects having one surface near to plane, on the basis of the 3D representation of their constituent fragments. The whole process starts by 3D scanning of the available fragments. The obtained representations are properly p…
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48 results for “Fragmented objects”
Automated rock fragmentation assessment using deep learning and spatial statistics.
problem Assessing post-blast rock fragmentation in real-time.
method Fine-tuned YOLO12l-seg model for instance segmentation, followed by spatial statistics.
result Framework accurately assesses rock fragmentation patterns in real-time.
Deep learning solves jigsaw puzzles by classifying fragment positions.
problem Automated reconstruction of archaeological fragments from jigsaw puzzles.
method Classifies relative positions of fragments using deep neural networks and local feature co-occurrences.
result Our method outperforms state-of-the-art by 25%.
Paper tackles curve pattern identification from fragmented cultural heritage objects.
problem Identify full design of curve patterns from fragmented cultural heritage objects.
method Two-stage matching algorithm combining template matching and CNN re-ranking.
result Proposed algorithm outperforms traditional methods in identifying curve patterns from fragmented objects.
SVH-PSL uses Stein Variational Gradient Descent and Hypernetworks to improve Pareto set learning for expensive MOO.
problem Fragmented surrogate models and pseudo-local optima in expensive multi-objective optimization problems.
method SVH-PSL integrates Stein Variational Gradient Descent (SVGD) with Hypernetworks to address fragmentation and pseudo-local optima.
result SVH-PSL significantly improves the quality of the learned Pareto set, offering a promising solution for expensive MOO.
Lower bound found for fragmentation norm, embedding provided.
problem Fragmentation norms on Hamiltonian diffeomorphisms of surfaces.
method Lower bound calculation and bi-Lipschitz embedding construction.
result Lower bound for fragmentation norm and embedding provided.
Proves homeomorphisms with positive fragmentation norm on complex manifolds.
problem Complex manifolds with intricate fundamental groups.
method Proves existence of measure-preserving homeomorphisms with positive fragmentation norm.
result Existence of homeomorphisms with positive stable fragmentation norm.
Study shows how adaptive traders decide between fragmented or consolidated markets based on venue demand.
problem Understanding market fragmentation and consolidation in adaptive trading systems.
method Analysis of adaptive traders choosing trading venues based on past experience, considering aggregate parameters like demand to supply ratio.
result Conditions for market fragmentation and stability of steady states are identified, showing fragmented states are metastable.
With a compact PL manifold X we associate a category T(X). The objects of T(X) are all combinatorial manifolds of type X, and morphisms are combinatorial assemblies. We prove that the homotopy equivalence BT (X) \approx BPL(X) holds, where PL(X) is the simplicial group of PL-homeomorphisms. Thus the space BT(X) is a ca…
A new deep model generates molecules by fragments, improving validity and uniqueness.
problem Generating valid and unique molecules using deep learning.
method Develops a language model for molecular fragments, using frequency-based masking.
result Significantly outperforms other language model-based competitors in molecule generation.
FluxLayer solves cross-chain liquidity fragmentation for better MEV capture.
problem Cross-chain fragmented liquidity and MEV optimization.
method Three-layer framework integrating settlement, intent, and leverage mechanisms.
result FluxLayer enhances cross-chain MEV by capturing more arbitrage opportunities.
FIRE method improves model performance in federated learning by penalizing fragmentation-induced covariate shifts.
problem Performance degradation in federated learning due to data fragmentation and covariate shift.
method FIRE method accumulates fragmentation-induced covariate shift divergences via approximate Fisher information and uses it as a per-fragment loss penalty.
result FIRE outperforms importance weighting and federated learning benchmarks by up to 5.3% on shifted validation sets.
SpeechYOLO detects and locates speech objects in audio signals.
problem Detecting and localizing speech in audio signals.
method Inspired by YOLO, SpeechYOLO uses a convolutional neural network with a least-mean-squares loss function.
result SpeechYOLO performs well on keyword spotting tasks, including read and spontaneous speech.
Study proves fluid limits of fragmented limit-order markets.
problem Modeling fragmented limit-order markets with small and frequent orders.
method Proved convergence of discrete system to fluid limit characterized by coupled nonlinear ODEs.
result Fluid system converges to stationary equilibrium state over time.
SILVR generates new molecules fitting protein binding sites.
problem Generating novel small molecule compounds for drug design.
method Selective Iterative Latent Variable Refinement (SILVR) for diffusion-based molecule generation.
result SILVR can generate new molecules similar in shape to original fragments without protein knowledge.
Proposes a new method for generating random parameters in neural networks.
problem Improving randomized learning of feedforward neural networks.
method Randomly selects slope angles, rotates activation functions, and distributes them across the input space.
result The method gives better results than the common approach, especially for complex target functions.
The sharp -fragmentation property for Hamiltonian diffeomorphisms and homeomorphisms on surfacesmath.SG
The paper shows how Hamiltonian diffeomorphisms and homeomorphisms can be broken down into smaller, manageable pieces.
problem Fragmenting Hamiltonian diffeomorphisms and homeomorphisms on surfaces.
method Develops a -fragmentation property for Hamiltonian diffeomorphisms and homeomorphisms on surfaces, proving it with a Lipschitz estimate.
result Hamiltonian diffeomorphisms and homeomorphisms can be decomposed into smaller, compactly supported pieces with a Lipschitz estimate on the -norm.
Tree structures are ubiquitous in data across many domains, and many datasets are naturally modelled by unobserved tree structures. In this paper, first we review the theory of random fragmentation processes [Bertoin, 2006], and a number of existing methods for modelling trees, including the popular nested Chinese rest…
MAS scores cluster size consistency from points, robust to label changes.
problem Desired uniformity in cluster sizes, stability under label perturbations.
method Mass Agreement Score (MAS) measures point-centric cluster size consistency, robust to label changes.
result MAS yields similar scores for partitions with similar bulk structure, sensitive to genuine redistribution of cluster mass.
New distribution simplifies covariance matrix inference.
problem Efficient inference for covariance matrices in large models.
method Incorporates Inverse G-Wishart distribution for variational message passing.
result Elegant and succinct expression of variational message passing fragments.
Fragment-based autoencoder improves molecule screening with little data.
problem Limited experimental data for molecular optimization.
method Fragment-based graphical autoencoding to generate structural fingerprints.
result Fragment-based autoencoding reduces prediction error in small data.
Machine learning classifies object code for target architecture and endianess.
problem Classifying un-labeled compiled code for analysis.
method Simple byte-value histograms and heuristic features from operands.
result High accuracy in classifying target architecture and endianess.
Fragmented exchanges arise due to speed advantages in high-activity regions.
problem Fragmentation of distributed securities exchanges due to speed advantages in high-activity regions.
method Economic model and Monte Carlo simulations of a decentralized exchange with two miner clusters.
result Speed advantage increases with infrastructure asymmetry between regions.
Model learns to sort music clips in sequence.
problem Finding an optimal permutation of music clips.
method Proposed a music puzzle game for self-supervised learning of neural networks.
result Improved architecture (SEN) performs better on music medley.
Random Fragments Classification of Microbial Marker Clades with Multi-class SVM and N-Best Algorithmq-bio.QM
SVM and N-best algorithm classify microbial marker clades from genome sequences.
problem Classifying microbial clades from genome sequences, especially new species.
method Support vector machine (SVM) with N-best algorithm, time series feature extraction, random fragment generation, k-mer size selection.
result Recognition accuracy rates above 28% in top-1 candidate, above 91% in top-10 candidate.
Model shows how multiple markets can coexist or fragment based on trader behavior.
problem Understanding market competition and coexistence among multiple trading venues.
method Stylized model of traders making repeated decisions at three markets, analyzed numerically and analytically.
result Parameters like memory length and choice intensity determine whether markets coexist or fragment.
New model integrates community and link clustering for network data.
problem Lack of embedded prior information and community evolution description in MMSB.
method Fragmentation coagulation process for community and link clustering, with Gibbs sampling for inference.
result Model infers community structure and evolution, improving MMSB.
High-fee pools attract more liquidity but execute less volume; low-fee pools have more stable LPs.
problem Optimal liquidity supply and execution on decentralized exchanges with fixed gas costs.
method Analysis of Uniswap data to compare high- and low-fee pools.
result Fragmented liquidity leads to more LPs and competition, improving overall market efficiency.
Study replicates market model, finds replication hindered by missing details.
problem Replicating a market model with missing details and limited quantitative reporting.
method Increased simulation runs, bootstrap confidence intervals, and code analysis.
result Achieved relational equivalence for most metrics but rejected quantitative alignment.
Diffeomorphisms of surfaces have many unbounded quasi-morphisms.
problem Understanding the quasi-morphisms on surface diffeomorphism groups.
method Constructing a hyperbolic graph and using it to deduce properties of the groups.
result The group is not uniformly perfect and its fragmentation norm is unbounded.
Study finds inefficiencies in US equity markets, especially with Dow 30 stocks.
problem Inefficiencies in US equity markets, particularly with Dow 30 stocks.
method Analyzed all quotes and trades associated with Dow 30 stocks in 2016 using comprehensive data.
result Fragmentation and dislocation of information feeds led to inefficiencies and opportunity costs.
The paper analyzes security issues in blockchain ecosystems with multiple SSPs and proposes two models for better stake management.
problem Security issues in blockchain ecosystems with multiple SSPs and stake fragmentation.
method Formalized the Multiple SSP Problem and analyzed two architectures: Model and Model through convex optimization and game-theoretic lens.
result Model achieves tighter security guarantees through single validator sets and aggregated slashing logic.
FREED++: Improving RL Agents for Fragment-Based Molecule Generation by Thorough Reproductionq-bio.BM
Improved RL model for fragment-based molecule generation.
problem Generating molecules with high docking scores.
method Thorough reproduction, scrutiny, and improvement of the FREED model.
result The improved model produces molecules with superior docking scores.
This paper extends quasimorphism results to nonorientable surfaces.
problem Understanding quasimorphisms on nonorientable surface diffeomorphism groups.
method Constructing infinitely many quasimorphisms on the identity component of nonorientable surface diffeomorphism groups.
result The space of nontrivial quasimorphisms on the identity component of the diffeomorphism group of a closed nonorientable surface is infinite-dimensional.
Paper introduces a method to predict molecule properties from diverse data sources.
problem Limited ability to accommodate scarce or fragmented training data.
method Adaptive Invariance using invariant risk minimization to generalize beyond heterogeneous data.
result Predictor outperforms state-of-the-art transfer learning methods by significant margin.
Pareto law, which states that wealth distribution in societies have a power-law tail, has been a subject of intensive investigations in statistical physics community. Several models have been employed to explain this behavior. However, most of the agent based models assume the conservation of number of agents and wealt…
DADC algorithm improves clustering for data with varying density.
problem Sparse cluster loss and cluster fragmentation in density peak clustering.
method Domain-adaptive density measurement, cluster center self-identification, and cluster self-ensemble.
result DADC achieves more reasonable clustering results on data with varying density.
We relate generalized Lebesgue decompositions of measures in terms of curve fragments (Alberti representations) and Weaver derivations. This correspondence leads to a geometric characterization of the local norm on the Weaver cotangent bundle of a metric measure space : the local norm of a form sees how fas…
Unified causal models are formed from fragmented data sets.
problem Combining fragmented data sets to form a unified causal explanation is challenging.
method Using conditional independence properties of marginal datasets to reduce the number of possible models.
result Reduces the number of possible models to a unique one in some cases.
Study examines Bitcoin market fragmentation and price formation, revealing market leader-lagger dynamics and trading strategies.
problem Understanding price formation in fragmented Bitcoin markets at sub-second time scales.
method Utilized granular orderbook and trades data, constructed features, and trained linear models to explain market returns.
result Fee regime determines market leadership and profitability of taker strategies, maker strategies tested in real-world trading.
A theoretical approach for Pareto-Zipf lawphysics.soc-ph
We suggest an analytical approach for Pareto-Zipf law, where we assume random multiplicative noise and fragmentation processes for the growth of the number of citizens of each city and the number of the cities, respectively.
Paper tackles transferring knowledge for learning distance metrics across different domains.
problem Mitigating label information deficiency in target distance metric learning.
method Develops a flexible HTDML framework that uses knowledge fragments from source domain to help target metric learning.
result Reduces generalization error in the target domain using the proposed transfer strategy.
A big challenge in algorithmic composition is to devise a model that is both easily trainable and able to reproduce the long-range temporal dependencies typical of music. Here we investigate how artificial neural networks can be trained on a large corpus of melodies and turned into automated music composers able to gen…
The paper extends Thurston's method to new variants of Mather-Thurston theorem.
problem Proving new variants of Mather-Thurston theorem for PL homeomorphisms and contactomorphisms.
method Generalizing Thurston's technique to prove new variants of Mather-Thurston theorem for PL homeomorphisms and contactomorphisms.
result The paper answers questions posed by Gelfand-Fuks and Greenberg on PL foliations and Rybicki on contactomorphisms.
It is shown that the compactly supported identity component of the diffeomorphism group of the 2-dimensional punctured torus is an unbounded group. It follows that the fragmentation norm of is unbounded.
Deep networks analyzed using IFS theory for stability and generalization.
problem Stability and generalization of deep neural networks.
method Viewing deep architectures as place-dependent IFS and applying results from random dynamical systems.
result Derivation of a Wasserstein generalization bound and a new training objective.
Neural network predicts electron-ionization mass spectra quickly.
problem Identifying unknown molecules not in existing libraries.
method Lightweight neural network model for predicting mass spectra.
result High accuracy predictions of small molecule mass spectra.
This study aims to improve communication between fragmented blockchain systems in finance.
problem Inefficient and insecure communication in fragmented blockchain systems.
method Analysis of cross-chain interoperability protocols and their properties.
result Comparison and evaluation of cross-chain interoperability protocols.