Saved in:
| Main Authors: | Csuzdi, Domonkos, Törő, Olivér, Bécsi, Tamás |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.16639 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Physics-informed neural particle flow for the Bayesian update step
by: Csuzdi, Domonkos, et al.
Published: (2026)
by: Csuzdi, Domonkos, et al.
Published: (2026)
A Variational Lagrangian Framework for Log-Homotopy Particle Flow Filters
by: Törő, Olivér, et al.
Published: (2026)
by: Törő, Olivér, et al.
Published: (2026)
An integration-free approach for particle flow filtering
by: Csuzdi, Domonkos, et al.
Published: (2026)
by: Csuzdi, Domonkos, et al.
Published: (2026)
Resampling-free Particle Filters in High-dimensions
by: Boopathy, Akhilan, et al.
Published: (2024)
by: Boopathy, Akhilan, et al.
Published: (2024)
Resampled Confidence Regions with Exponential Shrinkage for the Regression Function of Binary Classification
by: Tamás, Ambrus, et al.
Published: (2023)
by: Tamás, Ambrus, et al.
Published: (2023)
Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach
by: Jabbar, Zain, et al.
Published: (2026)
by: Jabbar, Zain, et al.
Published: (2026)
Resampling and averaging coordinates on data
by: Blumberg, Andrew J., et al.
Published: (2024)
by: Blumberg, Andrew J., et al.
Published: (2024)
Can Large Language Models Detect Methodological Flaws? Evidence from Gesture Recognition for UAV-Based Rescue Operation Based on Deep Learning
by: Varga, Domonkos
Published: (2026)
by: Varga, Domonkos
Published: (2026)
Controllable Generation via Locally Constrained Resampling
by: Ahmed, Kareem, et al.
Published: (2024)
by: Ahmed, Kareem, et al.
Published: (2024)
Correcting Diffusion Generation through Resampling
by: Liu, Yujian, et al.
Published: (2023)
by: Liu, Yujian, et al.
Published: (2023)
Improving Insurance Catastrophic Data with Resampling and GAN Methods
by: Dzadz, Norbert, et al.
Published: (2024)
by: Dzadz, Norbert, et al.
Published: (2024)
Normalizing Flow-based Differentiable Particle Filters
by: Chen, Xiongjie, et al.
Published: (2024)
by: Chen, Xiongjie, et al.
Published: (2024)
Towards a Distributed Federated Learning Aggregation Placement using Particle Swarm Intelligence
by: Ali-Pour, Amir, et al.
Published: (2025)
by: Ali-Pour, Amir, et al.
Published: (2025)
fastml: Guarded Resampling Workflows for Safer Automated Machine Learning in R
by: Korkmaz, Selcuk, et al.
Published: (2026)
by: Korkmaz, Selcuk, et al.
Published: (2026)
Thought Branches: Interpreting LLM Reasoning Requires Resampling
by: Macar, Uzay, et al.
Published: (2025)
by: Macar, Uzay, et al.
Published: (2025)
Regime Learning for Differentiable Particle Filters
by: Brady, John-Joseph, et al.
Published: (2024)
by: Brady, John-Joseph, et al.
Published: (2024)
Resampling Filter Design for Multirate Neural Audio Effect Processing
by: Carson, Alistair, et al.
Published: (2025)
by: Carson, Alistair, et al.
Published: (2025)
Leveraging Influence Functions for Resampling Data in Physics-Informed Neural Networks
by: Naujoks, Jonas R., et al.
Published: (2025)
by: Naujoks, Jonas R., et al.
Published: (2025)
Differentiable Adaptive Kalman Filtering via Optimal Transport
by: He, Yangguang, et al.
Published: (2025)
by: He, Yangguang, et al.
Published: (2025)
Differentiable Interacting Multiple Model Particle Filtering
by: Brady, John-Joseph, et al.
Published: (2024)
by: Brady, John-Joseph, et al.
Published: (2024)
Credit Scores: Performance and Equity
by: Albanesi, Stefania, et al.
Published: (2024)
by: Albanesi, Stefania, et al.
Published: (2024)
Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling
by: Guo, Yiran, et al.
Published: (2026)
by: Guo, Yiran, et al.
Published: (2026)
FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
by: Bachmann, Roman, et al.
Published: (2025)
by: Bachmann, Roman, et al.
Published: (2025)
How Weight Resampling and Optimizers Shape the Dynamics of Continual Learning and Forgetting in Neural Networks
by: Frati, Lapo, et al.
Published: (2025)
by: Frati, Lapo, et al.
Published: (2025)
Cascaded Learned Bloom Filter for Optimal Model-Filter Size Balance and Fast Rejection
by: Sato, Atsuki, et al.
Published: (2025)
by: Sato, Atsuki, et al.
Published: (2025)
Reject, Resample, Repeat: Understanding Parallel Reasoning in Language Model Inference
by: Golowich, Noah, et al.
Published: (2026)
by: Golowich, Noah, et al.
Published: (2026)
SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate
by: Wei, Lifu, et al.
Published: (2026)
by: Wei, Lifu, et al.
Published: (2026)
PyDPF: A Python Package for Differentiable Particle Filtering
by: Brady, John-Joseph, et al.
Published: (2025)
by: Brady, John-Joseph, et al.
Published: (2025)
Centered plug-in estimation of Wasserstein distances
by: Papp, Tamás P., et al.
Published: (2022)
by: Papp, Tamás P., et al.
Published: (2022)
SeRpEnt: Selective Resampling for Expressive State Space Models
by: Rando, Stefano, et al.
Published: (2025)
by: Rando, Stefano, et al.
Published: (2025)
PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding
by: Kuzucu, Selim, et al.
Published: (2026)
by: Kuzucu, Selim, et al.
Published: (2026)
Adversarial Transform Particle Filters
by: Gong, Chengxin, et al.
Published: (2025)
by: Gong, Chengxin, et al.
Published: (2025)
Escaping Local Optima in Global Placement
by: Xue, Ke, et al.
Published: (2024)
by: Xue, Ke, et al.
Published: (2024)
Exploring End-to-end Differentiable Neural Charged Particle Tracking -- A Loss Landscape Perspective
by: Kortus, Tobias, et al.
Published: (2024)
by: Kortus, Tobias, et al.
Published: (2024)
Interpolating Discrete Diffusion Models with Controllable Resampling
by: Kollovieh, Marcel, et al.
Published: (2026)
by: Kollovieh, Marcel, et al.
Published: (2026)
Variance Reduction via Resampling and Experience Replay
by: Han, Jiale, et al.
Published: (2025)
by: Han, Jiale, et al.
Published: (2025)
Reachability Weighted Offline Goal-conditioned Resampling
by: Yang, Wenyan, et al.
Published: (2025)
by: Yang, Wenyan, et al.
Published: (2025)
Towards Optimal Adapter Placement for Efficient Transfer Learning
by: Nowak, Aleksandra I., et al.
Published: (2024)
by: Nowak, Aleksandra I., et al.
Published: (2024)
Enhanced SMC$^2$: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals
by: Rosato, Conor, et al.
Published: (2024)
by: Rosato, Conor, et al.
Published: (2024)
The Limits of Inference Scaling Through Resampling
by: Stroebl, Benedikt, et al.
Published: (2024)
by: Stroebl, Benedikt, et al.
Published: (2024)
Similar Items
-
Physics-informed neural particle flow for the Bayesian update step
by: Csuzdi, Domonkos, et al.
Published: (2026) -
A Variational Lagrangian Framework for Log-Homotopy Particle Flow Filters
by: Törő, Olivér, et al.
Published: (2026) -
An integration-free approach for particle flow filtering
by: Csuzdi, Domonkos, et al.
Published: (2026) -
Resampling-free Particle Filters in High-dimensions
by: Boopathy, Akhilan, et al.
Published: (2024) -
Resampled Confidence Regions with Exponential Shrinkage for the Regression Function of Binary Classification
by: Tamás, Ambrus, et al.
Published: (2023)