parameter estimation

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 369 papers with code (1,719 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Variational Autoencoders for Collaborative Filtering
  16 Feb 2018 18 repositories listed Syntology ran 2 of 21 samples · 19 unverified · 1 pointer-only (licence)
  This non-linear probabilistic model enables us to go beyond the limited modeling capacity of linear factor models which still largely dominate collaborative filtering research.
• Contemporary Symbolic Regression Methods and their Relative Performance
  29 Jul 2021 5 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  We assess 14 symbolic regression methods and 7 machine learning methods on a set of 252 diverse regression problems.
• NeRF--: Neural Radiance Fields Without Known Camera Parameters
  14 Feb 2021 5 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
  Considering the problem of novel view synthesis (NVS) from only a set of 2D images, we simplify the training process of Neural Radiance Field (NeRF) on forward-facing scenes by removing the requirement of known or…
• Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs
  25 Aug 2017 5 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  For inference with Sequential Monte Carlo, this automatically yields improvements such as locally-optimal proposals and Rao-Blackwellization.
• Stable Architectures for Deep Neural Networks
  9 May 2017 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.
• Convolutional neural network architecture for geometric matching
  16 Mar 2017 5 repositories listed Syntology ran 2 of 14 samples · 12 unverified · 2 pointer-only (licence)
  We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine or thin-plate spline transformation, and estimating its parameters.
• Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes
  25 Aug 2017 4 repositories listed
  The main result of this paper is to show that improved parameter estimation allows BNCs to outperform leading learning methods such as Random Forest for both 0-1 loss and RMSE, albeit just on categorical datasets.
• The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
  21 May 2024 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  First, we demonstrate the application of this paradigm on a simulated cosmic shear analysis for a Stage IV survey in 37- and 39-dimensional parameter spaces, comparing ΛCDM and a dynamical dark energy model…
• BayesFlow: Learning complex stochastic models with invertible neural networks
  13 Mar 2020 3 repositories listed
  In addition, our method incorporates a summary network trained to embed the observed data into maximally informative summary statistics.
• Orthogonal Statistical Learning
  25 Jan 2019 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We provide non-asymptotic excess risk guarantees for statistical learning in a setting where the population risk with respect to which we evaluate the target parameter depends on an unknown nuisance parameter that must…
• Variational Autoencoders for Collaborative Filtering
  16 Feb 2018 3 repositories listed
  We introduce a generative model with multinomial likelihood and use Bayesian inference for parameter estimation.
• Notes on Noise Contrastive Estimation and Negative Sampling
  30 Oct 2014 3 repositories listed
  Estimating the parameters of probabilistic models of language such as maxent models and probabilistic neural models is computationally difficult since it involves evaluating partition functions by summing over an entire…
• Neural Parameter Estimation with Incomplete Data
  8 Jan 2025 2 repositories listed
  Leveraging their computational speed and flexibility, neural networks are also being used to facilitate fast, likelihood-free statistical inference.
• Tests for model misspecification in simulation-based inference: from local distortions to global model checks
  19 Dec 2024 2 repositories listed
  Model misspecification analysis strategies, such as anomaly detection, model validation, and model comparison are a key component of scientific model development.
• Extended Fiducial Inference: Toward an Automated Process of Statistical Inference
  31 Jul 2024 2 repositories listed
  The new method achieves the goal of fiducial inference by leveraging advanced statistical computing techniques while remaining scalable for big data.
• Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
  19 Feb 2024 2 repositories listed
  Ordinary differential equations (ODEs) are widely used to describe dynamical systems in science, but identifying parameters that explain experimental measurements is challenging.
• FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions
  26 Mar 2023 2 repositories listed
  We propose a new, flexible and ultra-efficient approach to perform feature selection in a sparse high dimensional function-on-function regression problem, and we show how to extend it to the scalar-on-function framework.
• Likelihood-Free Parameter Estimation with Neural Bayes Estimators
  27 Aug 2022 2 repositories listed
  Neural point estimators are neural networks that map data to parameter point estimates.
• Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
  3 Mar 2022 2 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  This paper introduces a new topic-modeling framework where each document is viewed as a set of word embedding vectors and each topic is modeled as an embedding vector in the same embedding space.
• Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
  3 Feb 2022 2 repositories listed
  The dynamics of systems biological processes are usually modeled by a system of ordinary differential equations (ODEs) with many unknown parameters that need to be inferred from noisy and sparse measurements.
• Scale-invariant Learning by Physics Inversion
  30 Sep 2021 2 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  We find that state-of-the-art training techniques are not well-suited to many problems that involve physical processes.
• Deep Learning-Based Estimation and Goodness-of-Fit for Large-Scale Confirmatory Item Factor Analysis
  20 Sep 2021 2 repositories listed
  We investigate novel parameter estimation and goodness-of-fit (GOF) assessment methods for large-scale confirmatory item factor analysis (IFA) with many respondents, items, and latent factors.
• A protocol for dynamic model calibration
  25 May 2021 2 repositories listed
  Here, we provide a protocol that guides the user through all the steps involved in the calibration of dynamic models.
• Bayesian multiscale deep generative model for the solution of high-dimensional inverse problems
  4 Feb 2021 2 repositories listed
  In this way, the global features are identified in the coarse-scale with inference of low-dimensional variables and inexpensive forward computation, and the local features are refined and corrected in the fine-scale.
• Memory AMP
  20 Dec 2020 2 repositories listed
  To asymptotically characterize the performance of BO-MAMP, a state evolution is derived.
• AMICI: High-Performance Sensitivity Analysis for Large Ordinary Differential Equation Models
  16 Dec 2020 2 repositories listed
  Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes.
• Noise-Contrastive Estimation for Multivariate Point Processes
  2 Nov 2020 2 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  The log-likelihood of a generative model often involves both positive and negative terms.
• Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop
  21 Jul 2020 2 repositories listed Syntology ran 0 of 14 samples · 14 unverified
  We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monocular internet images.
• Image Processing and Quality Control for Abdominal Magnetic Resonance Imaging in the UK Biobank
  2 Jul 2020 2 repositories listed
  An end-to-end image analysis pipeline is presented for the abdominal MRI protocol used in the UK Biobank on the first 38, 971 participants.
• On the automatic annotation of gene functions using observational data and phylogenetic trees
  14 May 2020 2 repositories listed
  While very simple, our model of gene-function evolution has some key features that have the potential to generate an impact in the field: (a) compared to other methods, ours is highly-scalable, which means that it is…

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.