First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models | Paper Citation Record

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This paper cites Jumper, R.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Jumper, R

Reference 1

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 2

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This paper cites Behler and M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Behler and M

Reference 3

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This paper cites Carleo and M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Carleo and M

Reference 4

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 5

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Reference 6

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This paper cites Anelli, H.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Anelli, H

Reference 7

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This paper cites Lagemann, K.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Lagemann, K

Reference 8

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This paper cites Ravuri, K.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Ravuri, K

Reference 9

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 10

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 11

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This paper cites Tsai, E.-J.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Tsai, E.-J

Reference 12

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Observation 98dd4eee-8575-45e7-9dcc-18092a94410c · outbound

This paper cites Geiger and C.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Geiger and C

Reference 13

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This paper cites Fukumizu and S.-i.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Fukumizu and S.-i

Reference 14

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This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 15

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 16

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This paper cites an unresolved cited work.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 17

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This paper cites Duchi, E.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Duchi, E

Reference 18

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This paper cites ADADELTA: An Adaptive Learning Rate Method.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models ADADELTA: An Adaptive Learning Rate Method

Reference 19

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This paper cites Adam: A Method for Stochastic Optimization.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Adam: A Method for Stochastic Optimization

Reference 20

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This paper cites Nguyen, S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Nguyen, S

Reference 21

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This paper cites Sutskever, J.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Sutskever, J

Reference 22

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This paper cites Leimkuhler, C.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Leimkuhler, C

Reference 23

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This paper cites Ash and R.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Ash and R

Reference 24

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This paper cites Zaidi, T.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Zaidi, T

Reference 25

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 26

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This paper cites Dohare, J.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Dohare, J

Reference 27

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This paper cites Feng and Y.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Feng and Y

Reference 28

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This paper cites Cheng, D.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Cheng, D

Reference 29

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This paper cites Charting the Topography of the Neural Network Landscape with Thermal-Like Noise.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Charting the Topography of the Neural Network Landscape with Thermal-Like Noise

Reference 30

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This paper cites TherML: Thermodynamics of Machine Learning.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models TherML: Thermodynamics of Machine Learning

Reference 31

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 32

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This paper cites Choromanska, M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Choromanska, M

Reference 33

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This paper cites Zdeborová, Understanding deep learning is also a job for physicists, Nature Physics16, 602 (2020).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Zdeborová, Understanding deep learning is also a job for physicists, Nature Physics16, 602 (2020)

Reference 34

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 35

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This paper cites Carleo, I.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Carleo, I

Reference 36

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This paper cites Stephan, M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Stephan, M

Reference 37

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This paper cites Universal Linear Response of First-Passage Kinetics: A Framework for Prediction and Inference.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Universal Linear Response of First-Passage Kinetics: A Framework for Prediction and Inference

Reference 38

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This paper cites Redner,A Guide to First-Passage Processes(Cambridge University Press, 2001).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Redner,A Guide to First-Passage Processes(Cambridge University Press, 2001)

Reference 39

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This paper cites Metzler, S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Metzler, S

Reference 40

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Observation 71a9e3d1-ca8a-4a0b-8ac4-153be3b1db0e · outbound

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 41

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This paper cites Krizhevsky, G.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Krizhevsky, G

Reference 42

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This paper cites Deng, The mnist database of handwritten digit images for machine learning research, IEEE Signal Processing Magazine29, 141 (2012).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Deng, The mnist database of handwritten digit images for machine learning research, IEEE Signal Processing Magazine29, 141 (2012)

Reference 43

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 44

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Observation 68dd9139-62ad-454e-85dc-fa38ff74c5de · outbound

This paper cites Reuveni, Optimal stochastic restart renders fluctuations in first passage times universal, Physical review letters116, 170601 (2016).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Reuveni, Optimal stochastic restart renders fluctuations in first passage times universal, Physical review letters116, 170601 (2016)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.393275Z

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This paper cites Pal and S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Pal and S

Reference 46

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Observation 64767e24-15e3-4c0f-ab2e-7335370ed0bc · outbound

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 47

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Observation b3228d3c-bb67-4586-9233-d638401babd0 · outbound

This paper cites Blumer, S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Blumer, S

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.368006Z

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This paper cites Blumer, S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Blumer, S

Reference 49

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This paper cites Eliazar and S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Eliazar and S

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.351126Z

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Observation 0d49b90a-62cd-41af-8461-796add9e6fab · outbound

This paper cites Nitzan,Chemical dynamics in condensed phases: relaxation, transfer, and reactions in condensed molecular systems (Oxford university press, 2024).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Nitzan,Chemical dynamics in condensed phases: relaxation, transfer, and reactions in condensed molecular systems (Oxford university press, 2024)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.343058Z

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Observation e7bf7aac-eb52-4c46-84ae-a81631f79caa · outbound

This paper cites an unresolved cited work.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 52

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First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 53

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Observation 1442a96f-83ed-4962-80c3-a8ec414ca303 · outbound

This paper cites Hanggi, Escape from a metastable state, Journal of Statistical Physics42, 105 (1986).

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Hanggi, Escape from a metastable state, Journal of Statistical Physics42, 105 (1986)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.321688Z

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Observation 5fe21dfb-2f79-44b7-924a-317b73392d4e · outbound

This paper cites Hänggi, P.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Hänggi, P

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.312658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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This paper cites Barducci, M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Barducci, M

Reference 56

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 08dea084-b57b-4d10-8be5-00d582a56268 · outbound

This paper cites Valsson and M.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Valsson and M

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.295464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f4f9e934-d2e0-480b-bd3c-f5e7d61208ab · outbound

This paper cites Bussi and A.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Bussi and A

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.285522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 558db043-0258-442f-9b4a-665e8ccaf183 · outbound

This paper cites an unresolved cited work.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Unresolved cited work

Reference 59

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 061145e6-7d91-433a-9165-24f2d4a128c0 · outbound

This paper cites Tiwary, J.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Tiwary, J

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.270049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 374287ce-6420-4bce-909d-c7ea0034cd4f · outbound

This paper cites Blumer, S.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Blumer, S

Reference 61

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e69b5784-26f5-4fbc-a2af-06d0f1db17a1 · outbound

This paper cites Dekel and L.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Dekel and L

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.252608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e7b206e0-c612-4e27-96ad-3fa72d206e75 · outbound

This paper cites Leclerc, A.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models Leclerc, A

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.243184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ecfe07c4-6f48-4a7a-a6a3-adb3e1769a4c · outbound

This paper cites S4, we show that the training process on the CIFAR-100 dataset also reaches a QSS.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models S4, we show that the training process on the CIFAR-100 dataset also reaches a QSS

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.233326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6117179b-4c1c-470a-9648-0f3d5f29257c · outbound

This paper cites S7, we show that the training process with a momentum term, on the CIFAR-100 dataset reaches a QSS.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models S7, we show that the training process with a momentum term, on the CIFAR-100 dataset reaches a QSS

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.224781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e68fdd7c-8eb7-4ecf-a985-c246fda580ae · outbound

This paper cites test accuracy.

First-Passage Approach to Optimizing Perturbations for Improved Training of Machine Learning Models test accuracy

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:31:32.215377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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