New algorithms improve Bayesian inference for SV models with leverage.
problem Efficient Bayesian estimation of SV models with leverage.
method Derive novel algorithms for centered and non-centered parameterizations, combine samplers using ASIS.
result Stable sampling efficiency irrespective of parameterization.
We show that one can interweave an unknot into any non-alternating connected projection of a link so that the resulting augmented projection is alternating.
Weaved helices form mechanically stable 3D structures.
problem Creating stable 3D structures from helical elements.
method Exploiting screw symmetry and invariant cylindrical rod packing to form triply periodic arrangements.
result Demonstrated nineteen triply periodic arrangements of interwoven helices.
Enhances drug discovery by optimizing molecular structures.
problem Accelerate drug discovery through better optimization of precursor molecules.
method Integrates substructure components with atom-level encoding in a fully autoregressive graph decoder.
result Significantly outperforms previous state-of-the-art baselines on molecular optimization tasks.
Paper analyzes patterns in African exports using network analysis.
problem Limited data on African countries in trade networks.
method Defined two bipartite networks and their minimal spanning trees.
result Emerging patterns reveal important characteristics of African exports.
Blockchain data improves asset predictions by 4x compared to LSTM.
problem Improving asset value predictions using blockchain data.
method Modern Deep Learning techniques applied to blockchain account distribution histograms and spatial dataset modeling.
result Error reduction of 4 times with blockchain data compared to LSTM approach. Paper proposes a novel method for aligning hierarchical data using optimal transport in hyperbolic spaces.
problem Aligning hierarchical data like ontologies without external supervision.
method Optimal transport over hyperbolic spaces.
result The method outperforms standard embedding alignment techniques.
Globalization processes interweave economic structures at a worldwide scale, trade playing a central role as one of the elemental channels of interaction among countries. Despite the significance of such phenomena, measuring economic globalization still remains an open problem. More quantitative treatments could improv…
Few-shot network compression improves accuracy with minimal data.
problem High estimation errors from original network during inference.
method Cross distillation, layer-wise knowledge distillation approach.
result Cross distillation significantly improves student network's accuracy with few training instances.
The study initiates a theoretical analysis of dynamic benchmarking models.
problem Lack of theoretical foundation and empirical studies in dynamic benchmarks.
method Examined two realizations of dynamic benchmarking: sequential and hierarchical dependency models.
result Sequential dynamic benchmarks show initial performance improvement but can stall after three rounds due to label noise.
This work improves SGD minibatch sampling using determinantal point processes based on orthogonal polynomials.
problem Improving variance reduction in stochastic gradient descent (SGD) for large datasets.
method Orthogonal polynomial-based determinantal point processes for sampling minibatches in SGD.
result DPP minibatches lead to a smaller mean square approximation error than uniform minibatches.
MBExplainer provides explanations for models combining graph embeddings and tabular features.
problem Explaining models using a mix of graph embeddings and tabular features.
method Model-agnostic approach using Shapley values and Monte Carlo Tree Search.
result MBExplainer efficiently finds human-readable explanations for model predictions.