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Paper Citation Record · LEDGER

From Classification to Regression: Using a Fruitfly to Solve Equations

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.27196.

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pith.paper-citation-record.v1
2607.27196 v1

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measured 42 of 42 reference resolution

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42 of 42 outbound references displayed

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Outbound references

Observation cdfbd3ef-9065-404e-a711-961291db10ae · outbound

This paper cites Reduced-order modeling: new approaches for computational physics.

From Classification to Regression: Using a Fruitfly to Solve Equations Reduced-order modeling: new approaches for computational physics

Reference 1

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This paper cites Model reduction and approximation: theory and algorithms.

From Classification to Regression: Using a Fruitfly to Solve Equations Model reduction and approximation: theory and algorithms

Reference 2

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From Classification to Regression: Using a Fruitfly to Solve Equations Model reduction for flow analysis and control

Reference 3

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This paper cites Kernel methods in machine learning.

From Classification to Regression: Using a Fruitfly to Solve Equations Kernel methods in machine learning

Reference 4

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From Classification to Regression: Using a Fruitfly to Solve Equations Kernel methods for pattern analysis

Reference 5

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From Classification to Regression: Using a Fruitfly to Solve Equations Gaussian processes for regression

Reference 6

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This paper cites A tutorial on gaussian process regression: Modelling, exploring, and exploiting functions.

From Classification to Regression: Using a Fruitfly to Solve Equations A tutorial on gaussian process regression: Modelling, exploring, and exploiting functions

Reference 7

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This paper cites An intuitive tutorial to gaussian process regression.

From Classification to Regression: Using a Fruitfly to Solve Equations An intuitive tutorial to gaussian process regression

Reference 8

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This paper cites Radial basis functions.

From Classification to Regression: Using a Fruitfly to Solve Equations Radial basis functions

Reference 9

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This paper cites A radial basis function method for the shallow water equations on a sphere.

From Classification to Regression: Using a Fruitfly to Solve Equations A radial basis function method for the shallow water equations on a sphere

Reference 10

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From Classification to Regression: Using a Fruitfly to Solve Equations Deep learning: Foundations and concepts

Reference 11

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This paper cites Understanding deep learning.

From Classification to Regression: Using a Fruitfly to Solve Equations Understanding deep learning

Reference 12

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This paper cites Deep learning with Python.

From Classification to Regression: Using a Fruitfly to Solve Equations Deep learning with Python

Reference 13

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This paper cites Testing the Manifold Hypothesis.

From Classification to Regression: Using a Fruitfly to Solve Equations Testing the Manifold Hypothesis

Reference 14

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From Classification to Regression: Using a Fruitfly to Solve Equations Geometry from a time series

Reference 15

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From Classification to Regression: Using a Fruitfly to Solve Equations Locally weighted regression: an approach to regression analysis by local fitting

Reference 16

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From Classification to Regression: Using a Fruitfly to Solve Equations The approximation power of moving least-squares

Reference 17

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From Classification to Regression: Using a Fruitfly to Solve Equations Analysis of moving least squares approximation revisited

Reference 18

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From Classification to Regression: Using a Fruitfly to Solve Equations The partition of unity finite element method: basic theory and applications

Reference 19

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From Classification to Regression: Using a Fruitfly to Solve Equations The partition of unity method

Reference 20

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From Classification to Regression: Using a Fruitfly to Solve Equations Probabilistic partition of unity networks for high-dimensional regression problems

Reference 21

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From Classification to Regression: Using a Fruitfly to Solve Equations A clustering technique for the identification of piecewise affine systems

Reference 22

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From Classification to Regression: Using a Fruitfly to Solve Equations Piecewise affine regression via recursive multiple least squares and multicategory discrimination

Reference 23

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From Classification to Regression: Using a Fruitfly to Solve Equations A piecewise linear regression and classification algorithm with application to learning and model predictive control of hybrid systems

Reference 24

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From Classification to Regression: Using a Fruitfly to Solve Equations Nonlinear model order reduction based on local reduced- order bases

Reference 25

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From Classification to Regression: Using a Fruitfly to Solve Equations Breaking the kolmogorov barrier in model reduction of fluid flows

Reference 26

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From Classification to Regression: Using a Fruitfly to Solve Equations Can a Fruit Fly Learn Word Embeddings?

Reference 27

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From Classification to Regression: Using a Fruitfly to Solve Equations Embedology

Reference 28

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From Classification to Regression: Using a Fruitfly to Solve Equations Adaptive mixtures of local experts

Reference 29

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From Classification to Regression: Using a Fruitfly to Solve Equations Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 30

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From Classification to Regression: Using a Fruitfly to Solve Equations Ensemble and Mixture-of-Experts DeepONets For Operator Learning

Reference 31

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From Classification to Regression: Using a Fruitfly to Solve Equations Regression by classification

Reference 32

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From Classification to Regression: Using a Fruitfly to Solve Equations Regression as classification

Reference 33

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From Classification to Regression: Using a Fruitfly to Solve Equations Cluster-based reduced-order modelling of a mixing layer

Reference 34

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From Classification to Regression: Using a Fruitfly to Solve Equations Cluster-based network modeling—from snapshots to complex dynamical systems

Reference 35

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From Classification to Regression: Using a Fruitfly to Solve Equations A multifidelity deep operator network approach to closure for multiscale systems

Reference 36

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From Classification to Regression: Using a Fruitfly to Solve Equations Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 37

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From Classification to Regression: Using a Fruitfly to Solve Equations Weighted Nadaraya–Watson regression estimation

Reference 38

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From Classification to Regression: Using a Fruitfly to Solve Equations A least squares radial basis function partition of unity method for solving pdes

Reference 39

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From Classification to Regression: Using a Fruitfly to Solve Equations A comprehensive survey of continual learning: Theory, method and application

Reference 40

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This paper cites A multifidelity approach to continual learning for physical systems.

From Classification to Regression: Using a Fruitfly to Solve Equations A multifidelity approach to continual learning for physical systems

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This paper cites Enhancing classification accuracy through chaos.

From Classification to Regression: Using a Fruitfly to Solve Equations Enhancing classification accuracy through chaos

Reference 42

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