The impact of allocation strategies in subset learning on the expressive power of neural networks | Paper Citation Record

Observation 657d6430-3bd4-4355-9257-79195d253727 · outbound

This paper cites Thirst regulates motivated behavior through modulation of brainwide neural population dynamics.

The impact of allocation strategies in subset learning on the expressive power of neural networks Thirst regulates motivated behavior through modulation of brainwide neural population dynamics

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.747971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b4f11b1e-3675-42c5-8619-352fc3601918 · outbound

This paper cites Level sets and extrema of random processes and fields.

The impact of allocation strategies in subset learning on the expressive power of neural networks Level sets and extrema of random processes and fields

Reference 2

Resolution: verified exact; doi, observed 2026-08-08T16:11:46.162863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5e836c03-24b8-47ee-8b2e-a3a317a7877d · outbound

This paper cites Recurrent neural networks as versatile tools of neuroscience research.

The impact of allocation strategies in subset learning on the expressive power of neural networks Recurrent neural networks as versatile tools of neuroscience research

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.738948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d42cea96-24a0-445f-9e98-b65800d503dc · outbound

This paper cites A map of anticipatory activity in mouse motor cortex.

The impact of allocation strategies in subset learning on the expressive power of neural networks A map of anticipatory activity in mouse motor cortex

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.730546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e7bb256-ecdc-4fc4-87c4-e55f6c07cc58 · outbound

This paper cites On the Expressive Power of Deep Learning: A Tensor Analysis.

The impact of allocation strategies in subset learning on the expressive power of neural networks On the Expressive Power of Deep Learning: A Tensor Analysis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:45.969646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb840a72-9483-4216-8dd7-133fe6a15caf · outbound

This paper cites Capacity and Trainability in Recurrent Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Capacity and Trainability in Recurrent Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:45.973770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 561be448-1a59-4610-9298-954e8feede17 · outbound

This paper cites Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition.

The impact of allocation strategies in subset learning on the expressive power of neural networks Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.722146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56bbb126-6744-4775-8123-115a2e81a5d5 · outbound

This paper cites an unresolved cited work.

The impact of allocation strategies in subset learning on the expressive power of neural networks Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-08T16:12:31.713252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b0b4f8b-2024-491b-94da-4ff28146895a · outbound

This paper cites Targeted photostimulation uncovers circuit motifs supporting short-term memory.

The impact of allocation strategies in subset learning on the expressive power of neural networks Targeted photostimulation uncovers circuit motifs supporting short-term memory

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.704882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 08ca4648-043b-4629-b11f-bcb26777cd34 · outbound

This paper cites Finding structure in time.

The impact of allocation strategies in subset learning on the expressive power of neural networks Finding structure in time

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:45.986254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf27834c-4bf9-4fe0-a1bc-4ca301c2c666 · outbound

This paper cites Adversarial Reprogramming of Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Adversarial Reprogramming of Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:45.989204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b8bc65-ada3-467c-92b1-d9ce47ea2c8d · outbound

This paper cites Adversarial Reprogramming Revisited.

The impact of allocation strategies in subset learning on the expressive power of neural networks Adversarial Reprogramming Revisited

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-08T16:12:31.528729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d3a37d32-a0ad-4b17-9aa7-334863b21699 · outbound

This paper cites Connectivity underlying motor cortex activity during naturalistic goal-directed behavior.

The impact of allocation strategies in subset learning on the expressive power of neural networks Connectivity underlying motor cortex activity during naturalistic goal-directed behavior

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.689997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4b2badcf-0e7f-43e6-8585-5851276d9d63 · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:45.997704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53b11dc5-4bed-4b72-9beb-441532fbe992 · outbound

This paper cites Three unfinished works on the optimal storage capacity of networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Three unfinished works on the optimal storage capacity of networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.000898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff89c698-7111-4163-8de0-ba3202f95ce3 · outbound

This paper cites The Expressive Power of Tuning Only the Normalization Layers.

The impact of allocation strategies in subset learning on the expressive power of neural networks The Expressive Power of Tuning Only the Normalization Layers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.003613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7838acaa-e838-4641-b511-077621ac80ec · outbound

This paper cites Parameter-Efficient Transfer Learning with Diff Pruning.

The impact of allocation strategies in subset learning on the expressive power of neural networks Parameter-Efficient Transfer Learning with Diff Pruning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.006589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a81fee-9ee7-4f9c-8f28-fe2e6238a23f · outbound

This paper cites Labelling and optical erasure of synaptic memory traces in the motor cortex.

The impact of allocation strategies in subset learning on the expressive power of neural networks Labelling and optical erasure of synaptic memory traces in the motor cortex

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.681104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 92c08cad-12f2-4d76-bb45-5d8b4a3ff7b6 · outbound

This paper cites Heij, A.C.M.

The impact of allocation strategies in subset learning on the expressive power of neural networks Heij, A.C.M

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.671941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ad01171d-b7ac-4f98-af0f-c8b4d25adb6f · outbound

This paper cites Neural networks and physical systems with emergent collective computational abilities.

The impact of allocation strategies in subset learning on the expressive power of neural networks Neural networks and physical systems with emergent collective computational abilities

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.015591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcfbea6f-0d05-450a-801a-5c22b75678e0 · outbound

This paper cites Horn and Charles R.

The impact of allocation strategies in subset learning on the expressive power of neural networks Horn and Charles R

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.657413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3184fa93-0ba0-49ce-89ab-b9e75c1e226a · outbound

This paper cites Multilayer feedforward networks are universal approximators.

The impact of allocation strategies in subset learning on the expressive power of neural networks Multilayer feedforward networks are universal approximators

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.021284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08cf2d93-915e-4be2-ab80-d4595af65d60 · outbound

This paper cites The next generation of approaches to investigate the link between synaptic plasticity and learning.

The impact of allocation strategies in subset learning on the expressive power of neural networks The next generation of approaches to investigate the link between synaptic plasticity and learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.648674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a0180c4a-e2fb-4844-8319-55ca774207d9 · outbound

This paper cites Bci learning phenomena can be explained by gradient-based optimization.

The impact of allocation strategies in subset learning on the expressive power of neural networks Bci learning phenomena can be explained by gradient-based optimization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.639711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b6daeb80-7bf4-41a9-b51f-10ddb7217b47 · outbound

This paper cites On the Expressive Power of Geometric Graph Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks On the Expressive Power of Geometric Graph Neural Networks

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T16:12:16.448213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 239fb816-a744-4ed0-9333-ee38cecba0b5 · outbound

This paper cites Expressive power of recurrent neural networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Expressive power of recurrent neural networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.032703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b640e5c9-7073-40e1-9264-ba6ac8431a67 · outbound

This paper cites Kim, Arseny Finkelstein, Carson C.

The impact of allocation strategies in subset learning on the expressive power of neural networks Kim, Arseny Finkelstein, Carson C

Reference 27

Resolution: verified exact; doi, observed 2026-08-08T16:11:46.147114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 183fb14f-7871-4234-bdc5-789d1f57bff3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

The impact of allocation strategies in subset learning on the expressive power of neural networks Adam: A Method for Stochastic Optimization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.038690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6bbba82-903d-4761-bb47-cbf4eb739b12 · outbound

This paper cites Proving the Lottery Ticket Hypothesis: Pruning is All You Need.

The impact of allocation strategies in subset learning on the expressive power of neural networks Proving the Lottery Ticket Hypothesis: Pruning is All You Need

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-08T16:12:16.416808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0d8b0f5a-e18e-4202-938a-c8d361f16c67 · outbound

This paper cites PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning.

The impact of allocation strategies in subset learning on the expressive power of neural networks PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.044751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8c25f34-005c-4cf5-ae1c-13b5840c63d6 · outbound

This paper cites Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights.

The impact of allocation strategies in subset learning on the expressive power of neural networks Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.047526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6067268c-7c71-439d-b8c8-7b73bbcf2bbd · outbound

This paper cites Cortical layer--specific critical dynamics triggering perception.

The impact of allocation strategies in subset learning on the expressive power of neural networks Cortical layer--specific critical dynamics triggering perception

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.630406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9fdb45b3-e3a0-4854-8cdb-f2d02c11e721 · outbound

This paper cites Synaptic plasticity and memory: an evaluation of the hypothesis.

The impact of allocation strategies in subset learning on the expressive power of neural networks Synaptic plasticity and memory: an evaluation of the hypothesis

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.621168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e3e3b201-32a8-4aa1-9a83-cee93919fcea · outbound

This paper cites On the Number of Linear Regions of Deep Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks On the Number of Linear Regions of Deep Neural Networks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.056357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 412c2b68-479e-48f4-acc7-a46ee63e6784 · outbound

This paper cites Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics.

The impact of allocation strategies in subset learning on the expressive power of neural networks Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.613000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 967d6b3f-9a22-400e-81d8-9bb198919690 · outbound

This paper cites On the Expressive Power of Deep Neural Networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks On the Expressive Power of Deep Neural Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.062877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abcf3b3f-3680-42bd-97b5-c2f951acefa0 · outbound

This paper cites Targeted activation of hippocampal place cells drives memory-guided spatial behavior.

The impact of allocation strategies in subset learning on the expressive power of neural networks Targeted activation of hippocampal place cells drives memory-guided spatial behavior

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.604138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ef47eeff-466d-44a9-82bc-f92df961fe8b · outbound

This paper cites An analytical theory of curriculum learning in teacher-student networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks An analytical theory of curriculum learning in teacher-student networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.595583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fb8e4e09-6980-4712-81c6-59ae5cccb61c · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.072210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ca3ebe-4a4d-4d6e-8cae-d79635d997b4 · outbound

This paper cites Overcoming catastrophic forgetting with hard attention to the task.

The impact of allocation strategies in subset learning on the expressive power of neural networks Overcoming catastrophic forgetting with hard attention to the task

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.074773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c68534be-cc3a-41a8-96cb-9a22e55d447c · outbound

This paper cites Siegelmann and E.D.

The impact of allocation strategies in subset learning on the expressive power of neural networks Siegelmann and E.D

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.077786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f76e73ab-eaa2-4fab-b1b9-ff410664ae99 · outbound

This paper cites Mathematical problems for the next century.

The impact of allocation strategies in subset learning on the expressive power of neural networks Mathematical problems for the next century

Reference 42

Resolution: verified exact; doi, observed 2026-08-08T16:11:46.138414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1dd26141-ced0-4669-b36f-9ede40ea3f5d · outbound

This paper cites Distributed coding of choice, action and engagement across the mouse brain.

The impact of allocation strategies in subset learning on the expressive power of neural networks Distributed coding of choice, action and engagement across the mouse brain

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.587215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 64819185-03e7-4095-8268-03c3983d178c · outbound

This paper cites Concentration for the zero set of large random polynomial systems.

The impact of allocation strategies in subset learning on the expressive power of neural networks Concentration for the zero set of large random polynomial systems

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-08T16:12:01.301896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e9df0622-c8be-46af-9563-28cf55acb6fb · outbound

This paper cites Training Neural Networks with Fixed Sparse Masks.

The impact of allocation strategies in subset learning on the expressive power of neural networks Training Neural Networks with Fixed Sparse Masks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.089474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f1e5748-9014-4869-a00a-6a08ce1496d5 · outbound

This paper cites Spdf: sparse pre-training and dense fine-tuning for large language models.

The impact of allocation strategies in subset learning on the expressive power of neural networks Spdf: sparse pre-training and dense fine-tuning for large language models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.577823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d7bd026-ee08-4764-a71b-63c835beac8c · outbound

This paper cites Optical interrogation of multi-scale neuronal plasticity underlying behavioral learning.

The impact of allocation strategies in subset learning on the expressive power of neural networks Optical interrogation of multi-scale neuronal plasticity underlying behavioral learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.568450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d020ca52-96ca-4cf7-b4c8-21d4350f1402 · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

The impact of allocation strategies in subset learning on the expressive power of neural networks A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.098179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41d4cfb0-7034-4d25-91fd-259b538edd32 · outbound

This paper cites Supermasks in Superposition.

The impact of allocation strategies in subset learning on the expressive power of neural networks Supermasks in Superposition

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.101237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c132fa33-0180-4be6-9701-3edef01c3ffc · outbound

This paper cites Adahessian: An adaptive second order optimizer for machine learning.

The impact of allocation strategies in subset learning on the expressive power of neural networks Adahessian: An adaptive second order optimizer for machine learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:12:31.559216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d90cd0b-db6e-4932-8f9b-8c821e872261 · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models, 2022.

The impact of allocation strategies in subset learning on the expressive power of neural networks Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models, 2022

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.106765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 325e0aab-bde8-4d87-a78c-b91a0f83f94f · outbound

This paper cites The Expressive Power of Low-Rank Adaptation.

The impact of allocation strategies in subset learning on the expressive power of neural networks The Expressive Power of Low-Rank Adaptation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:46.109289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers