Saved in:
| Main Authors: | Chen, Shirui, Recanatesi, Stefano, Shea-Brown, Eric |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.01770 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Embed Distributions via Maximum Kernel Entropy
by: Kachaiev, Oleksii, et al.
Published: (2024)
by: Kachaiev, Oleksii, et al.
Published: (2024)
Linearity-based neural network compression
by: Dobler, Silas, et al.
Published: (2025)
by: Dobler, Silas, et al.
Published: (2025)
LayerCollapse: Adaptive compression of neural networks
by: Shabgahi, Soheil Zibakhsh, et al.
Published: (2023)
by: Shabgahi, Soheil Zibakhsh, et al.
Published: (2023)
Variational autoencoder-based neural network model compression
by: Cheng, Liang, et al.
Published: (2024)
by: Cheng, Liang, et al.
Published: (2024)
KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
by: Hazelden, James, et al.
Published: (2025)
by: Hazelden, James, et al.
Published: (2025)
Addressing divergent representations from causal interventions on neural networks
by: Grant, Satchel, et al.
Published: (2025)
by: Grant, Satchel, et al.
Published: (2025)
Elimination-compensation pruning for fully-connected neural networks
by: Ballini, Enrico, et al.
Published: (2026)
by: Ballini, Enrico, et al.
Published: (2026)
Distill n' Explain: explaining graph neural networks using simple surrogates
by: Pereira, Tamara, et al.
Published: (2023)
by: Pereira, Tamara, et al.
Published: (2023)
Why are hyperbolic neural networks effective? A study on hierarchical representation capability
by: Tan, Shicheng, et al.
Published: (2024)
by: Tan, Shicheng, et al.
Published: (2024)
Perturbation: A simple and efficient adversarial tracer for representation learning in language models
by: Rozner, Joshua, et al.
Published: (2026)
by: Rozner, Joshua, et al.
Published: (2026)
Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks
by: Hamreras, Safa, et al.
Published: (2025)
by: Hamreras, Safa, et al.
Published: (2025)
dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning
by: Chen, Shirui, et al.
Published: (2025)
by: Chen, Shirui, et al.
Published: (2025)
Advanced atom-level representations for protein flexibility prediction utilizing graph neural networks
by: Sarparast, Sina, et al.
Published: (2024)
by: Sarparast, Sina, et al.
Published: (2024)
Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networks
by: Shao, Yuxiu, et al.
Published: (2024)
by: Shao, Yuxiu, et al.
Published: (2024)
FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection
by: Zhao, Yunfeng, et al.
Published: (2025)
by: Zhao, Yunfeng, et al.
Published: (2025)
Implicit neural representation of textures
by: Kwok, Albert, et al.
Published: (2026)
by: Kwok, Albert, et al.
Published: (2026)
Task complexity shapes internal representations and robustness in neural networks
by: Jankowski, Robert, et al.
Published: (2025)
by: Jankowski, Robert, et al.
Published: (2025)
Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation
by: Li, Shiyuan, et al.
Published: (2024)
by: Li, Shiyuan, et al.
Published: (2024)
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)
by: Pan, Sheng, et al.
Published: (2026)
Implicit neural representations as a coordinate-based framework for continuous environmental field reconstruction from sparse ecological observations
by: Pregowska, Agnieszka, et al.
Published: (2026)
by: Pregowska, Agnieszka, et al.
Published: (2026)
Evaluating alignment between humans and neural network representations in image-based learning tasks
by: Demircan, Can, et al.
Published: (2023)
by: Demircan, Can, et al.
Published: (2023)
Decision-focused Graph Neural Networks for Combinatorial Optimization
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Discrete, compositional, and symbolic representations through attractor dynamics
by: Nam, Andrew, et al.
Published: (2023)
by: Nam, Andrew, et al.
Published: (2023)
Human alignment of neural network representations
by: Muttenthaler, Lukas, et al.
Published: (2022)
by: Muttenthaler, Lukas, et al.
Published: (2022)
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning
by: Wu, Hongfei, et al.
Published: (2024)
by: Wu, Hongfei, et al.
Published: (2024)
Deep Learning for Time Series Anomaly Detection: A Survey
by: Darban, Zahra Zamanzadeh, et al.
Published: (2022)
by: Darban, Zahra Zamanzadeh, et al.
Published: (2022)
Knowledge-aware contrastive heterogeneous molecular graph learning
by: Chen, Mukun, et al.
Published: (2025)
by: Chen, Mukun, et al.
Published: (2025)
Graph Sparsification via Mixture of Graphs
by: Zhang, Guibin, et al.
Published: (2024)
by: Zhang, Guibin, et al.
Published: (2024)
Outlier-robust neural network training: variation regularization meets trimmed loss to prevent functional breakdown
by: Okuno, Akifumi, et al.
Published: (2023)
by: Okuno, Akifumi, et al.
Published: (2023)
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
by: Zhang, He, et al.
Published: (2022)
by: Zhang, He, et al.
Published: (2022)
INSPIRE-GNN: Intelligent Sensor Placement to Improve Sparse Bicycling Network Prediction via Reinforcement Learning Boosted Graph Neural Networks
by: Gupta, Mohit, et al.
Published: (2025)
by: Gupta, Mohit, et al.
Published: (2025)
Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphs
by: Yan, Hao, et al.
Published: (2026)
by: Yan, Hao, et al.
Published: (2026)
How connectivity structure shapes rich and lazy learning in neural circuits
by: Liu, Yuhan Helena, et al.
Published: (2023)
by: Liu, Yuhan Helena, et al.
Published: (2023)
Making deep neural networks right for the right scientific reasons by interacting with their explanations
by: Schramowski, Patrick, et al.
Published: (2020)
by: Schramowski, Patrick, et al.
Published: (2020)
Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensemble
by: Xue, Yunzhe, et al.
Published: (2024)
by: Xue, Yunzhe, et al.
Published: (2024)
ST-TGExplainer: Disentangling Stability and Transition Patterns for Temporal GNN Interpretability
by: Chen, Hongjiang, et al.
Published: (2026)
by: Chen, Hongjiang, et al.
Published: (2026)
FedPFT: Federated Proxy Fine-Tuning of Foundation Models
by: Peng, Zhaopeng, et al.
Published: (2024)
by: Peng, Zhaopeng, et al.
Published: (2024)
On the transferability of Sparse Autoencoders for interpreting compressed models
by: Gupte, Suchit, et al.
Published: (2025)
by: Gupte, Suchit, et al.
Published: (2025)
Geometry-aware similarity metrics for neural representations on Riemannian and statistical manifolds
by: Cayco-Gajic, N Alex, et al.
Published: (2026)
by: Cayco-Gajic, N Alex, et al.
Published: (2026)
JaxUED: A simple and useable UED library in Jax
by: Coward, Samuel, et al.
Published: (2024)
by: Coward, Samuel, et al.
Published: (2024)
Similar Items
-
Learning to Embed Distributions via Maximum Kernel Entropy
by: Kachaiev, Oleksii, et al.
Published: (2024) -
Linearity-based neural network compression
by: Dobler, Silas, et al.
Published: (2025) -
LayerCollapse: Adaptive compression of neural networks
by: Shabgahi, Soheil Zibakhsh, et al.
Published: (2023) -
Variational autoencoder-based neural network model compression
by: Cheng, Liang, et al.
Published: (2024) -
KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
by: Hazelden, James, et al.
Published: (2025)