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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.

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48 results for source traces

This paper develops source traces for faster TD learning.

problem Improving temporal difference learning speed and generalization.
method Introduces source traces as a backward view of successor representations, enabling TD errors to be propagated to potential causal states.
result Demonstrates faster generalization and improved performance of source traces compared to previous methods.

The paper proposes using non-isotropic distances for more accurate trace link recommendation.

problem Time-consuming and error-prone creation and maintenance of trace links.
method Geometric viewpoint on semantic similarity using non-linear similarity measures.
result Non-isotropic distances improve trace link recommendation accuracy.

TRACE analyzes risk changes in models trained on shifted data.

problem Understanding performance changes when a model trained on shifted data is used.
method TRACE framework decomposes risk change into four factors: generalization gaps, model change penalty, and covariate shift penalty.
result TRACE provides a diagnostic tool to understand and quantify risk changes due to covariate shift.

FlowGN tackles graph representation learning by tracing information flow paths.

problem GCNs struggle with over-smoothing and scalability issues.
method FlowGN introduces a 'Sourceo oSink' mode and 'information flow path' concept.
result FlowGN outperforms state-of-the-art GCNs in public datasets.

An important preprocessing step in most data analysis pipelines aims to extract a small set of sources that explain most of the data. Currently used algorithms for blind source separation (BSS), however, often fail to extract the desired sources and need extensive cross-validation. In contrast, their rarely used probab…

2018-03-23abs ↗pdf ↗

Motivated by the work of Leininger on hyperbolic equivalence of homotopy classes of closed curves on surfaces, we investigate a similar phenomenon for free groups. Namely, we study the situation when two elements g,hg,h in a free group FF have the property that for every free isometric action of FF on an R\mathbb{R}-…

2004-09-16abs ↗pdf ↗

The study quantifies geometric differences between axonal branches using splines.

problem Neuromorphology's focus on macroscopic features neglects neuron internal geometry.
method Fitting splines to neuron traces, using Frenet-Serret formulas to compute curvature and torsion.
result Parameters of curvature and torsion are distributed differently between axonal branches.

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.

Corporate bond factor research is flawed due to measurement errors and ex-post filtering.

problem Replication crisis in corporate bond factor research.
method Analysis of 108 signals across nine thematic clusters, correction of transaction prices and return filtering.
result Majority of previously documented factors do not produce statistically significant alphas after correction.

Neural networks combining multiple data sources can reverse preferences, affecting decision reliability.

problem Preference reversals in neural networks under pooled data.
method Formalized through Case-Based Decision Theory, analyzed Gram geometry, introduced regularization, and developed auditing methods.
result Pooled refitting can reverse shared preferences, and conditions for preserving preferences are derived.

DiAMoNDBack models protein backmapping from coarse-grained Cα traces.

problem Restoring all-atom details from coarse-grained protein representations.
method Autoregressive denoising diffusion model for residue-by-residue backmapping.
result Achieves state-of-the-art reconstruction performance in diverse applications.

Derives Selberg trace formula on Riemann surfaces and generalizes to other spaces.

problem Deriving and generalizing the Selberg trace formula.
method Supersymmetric localization principle and path integral derivation.
result Derives Selberg trace formula on arbitrary compact Riemann surfaces and generic compact locally symmetric spaces.

CausalSim corrects bias in trace-driven simulations for more accurate results.

problem Bias in trace-driven simulations due to system conditions during trace collection.
method CausalSim learns a causal model of system dynamics and latent factors from an RCT to remove bias from trace data.
result CausalSim reduces simulation errors by 53% and 61% compared to baselines, providing more accurate insights.

This paper investigates the strength of the trace field as a commensurability invariant of hyperbolic 3-manifolds. We construct an infinite family of two-component hyperbolic link complements which are pairwise incommensurable and have the same trace field, and infinitely many 1-cusped finite volume hyperbolic 3-manifo…

2007-08-08abs ↗pdf ↗

Clarifies a trace for Heisenberg operators on contact manifolds.

problem Calculating the index of Heisenberg elliptic operators on contact manifolds.
method Introduced a new trace on Heisenberg pseudodifferential operators and constructed a cocycle in periodic cyclic cohomology.
result Simplified the construction of the trace on Heisenberg pseudodifferential operators.

Researchers compute trace formula for magnetic Laplacian on hyperbolic surfaces.

problem Analyzing the magnetic Laplacian on compact hyperbolic surfaces.
method Computed the trace formula for magnetic Laplacian energies above the Mane critical level.
result Asymptotic behavior of trace formula coefficients near the Mane critical level.

Researchers show how to secretly train models with hidden data, detect usage with high confidence.

problem Protecting training data from traceability in large language models.
method Gradient-based optimization to learn secret sequences absent from training data.
result Secret sequences can be learned by models without performance degradation, detectable with high confidence.

Introduces expected eligibility traces for more efficient credit assignment in reinforcement learning.

problem Efficiently assigning credit to states and actions in reinforcement learning.
method Introduces expected eligibility traces, allowing updates to counterfactual sequences.
result Substantial improvements in temporal-difference learning can be achieved with expected traces.

We study new invariants of elliptic partial differential operators acting on sections of a vector bundle over a closed Riemannian manifold that we call the relativistic heat trace and the quantum heat traces. We obtain some reduction formulas expressing these new invariants in terms of some integral transforms of the u…

2016-11-11abs ↗pdf ↗

New hyperbolic manifolds found with same trace ring.

problem Finding non-commensurable hyperbolic manifolds with identical trace rings.
method Proved existence of infinitely many non-commensurable manifolds with same ambient group and trace ring.
result Infinitely many non-commensurable hyperbolic manifolds with the same ambient group and trace ring.

Sub-Riemannian Selberg trace formulae for compact quotients of SL(2, R)

problem Computing zeta-regularized determinants of sub-Laplacians
method Using Fourier decomposition and Selberg trace formulae
result Compact determinant formula expressed in terms of base hyperbolic surface and relative Selberg product