Saved in:
| Main Authors: | Gupta, Vima, Varma, Sashank |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2311.15194 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Are More Tokens Rational? Inference-Time Scaling in Language Models as Adaptive Resource Rationality
by: Hu, Zhimin, et al.
Published: (2026)
by: Hu, Zhimin, et al.
Published: (2026)
Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning
by: Lian, Xin, et al.
Published: (2024)
by: Lian, Xin, et al.
Published: (2024)
Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments
by: Gandhi, Atith, et al.
Published: (2024)
by: Gandhi, Atith, et al.
Published: (2024)
A Distributional Analogue to the Successor Representation
by: Wiltzer, Harley, et al.
Published: (2024)
by: Wiltzer, Harley, et al.
Published: (2024)
The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis
by: Pham, Hoang, et al.
Published: (2025)
by: Pham, Hoang, et al.
Published: (2025)
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations
by: Stoewer, Paul, et al.
Published: (2023)
by: Stoewer, Paul, et al.
Published: (2023)
Decoupling Exploration and Exploitation for Unsupervised Pre-training with Successor Features
by: Kim, JaeYoon, et al.
Published: (2024)
by: Kim, JaeYoon, et al.
Published: (2024)
Stacked Universal Successor Feature Approximators for Safety in Reinforcement Learning
by: Cannon, Ian, et al.
Published: (2024)
by: Cannon, Ian, et al.
Published: (2024)
Proto Successor Measure: Representing the Behavior Space of an RL Agent
by: Agarwal, Siddhant, et al.
Published: (2024)
by: Agarwal, Siddhant, et al.
Published: (2024)
Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning
by: Wang, Changhong, et al.
Published: (2024)
by: Wang, Changhong, et al.
Published: (2024)
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
by: Jain, Arnav Kumar, et al.
Published: (2024)
by: Jain, Arnav Kumar, et al.
Published: (2024)
Feature Learning Dynamics in Infinite-Depth Neural Networks
by: Yao, Zihan, et al.
Published: (2025)
by: Yao, Zihan, et al.
Published: (2025)
Understanding the Functional Roles of Modelling Components in Spiking Neural Networks
by: Yin, Huifeng, et al.
Published: (2024)
by: Yin, Huifeng, et al.
Published: (2024)
Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)
by: Ngo, Giang, et al.
Published: (2026)
On the Structural Limitations of Weight-Based Neural Adaptation and the Role of Reversible Behavioral Learning
by: Konduru, Pardhu Sri Rushi Varma
Published: (2026)
by: Konduru, Pardhu Sri Rushi Varma
Published: (2026)
Learning Successor Features with Distributed Hebbian Temporal Memory
by: Dzhivelikian, Evgenii, et al.
Published: (2023)
by: Dzhivelikian, Evgenii, et al.
Published: (2023)
Hierarchical Active Inference using Successor Representations
by: Rangarajan, Prashant, et al.
Published: (2026)
by: Rangarajan, Prashant, et al.
Published: (2026)
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis
by: Kumar, Akash, et al.
Published: (2025)
by: Kumar, Akash, et al.
Published: (2025)
AcquisitionSynthesis: Targeted Data Generation using Acquisition Functions
by: Agarwal, Ishika, et al.
Published: (2026)
by: Agarwal, Ishika, et al.
Published: (2026)
Understanding Pooling in Graph Neural Networks
by: Grattarola, Daniele, et al.
Published: (2021)
by: Grattarola, Daniele, et al.
Published: (2021)
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
by: Myers, Vivek, et al.
Published: (2024)
by: Myers, Vivek, et al.
Published: (2024)
Modeling Understanding of Story-Based Analogies Using Large Language Models
by: Inani, Kalit, et al.
Published: (2025)
by: Inani, Kalit, et al.
Published: (2025)
Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics
by: Grillotti, Luca, et al.
Published: (2024)
by: Grillotti, Luca, et al.
Published: (2024)
Informing Acquisition Functions via Foundation Models for Molecular Discovery
by: Chen, Qi, et al.
Published: (2025)
by: Chen, Qi, et al.
Published: (2025)
Improving Noise Robustness through Abstractions and its Impact on Machine Learning
by: Ibias, Alfredo, et al.
Published: (2024)
by: Ibias, Alfredo, et al.
Published: (2024)
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime
by: Shilton, Alistair, et al.
Published: (2024)
by: Shilton, Alistair, et al.
Published: (2024)
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
SRNN: Spatiotemporal Relational Neural Network for Intuitive Physics Understanding
by: Yang, Fei
Published: (2025)
by: Yang, Fei
Published: (2025)
Understanding Task Representations in Neural Networks via Bayesian Ablation
by: Nam, Andrew, et al.
Published: (2025)
by: Nam, Andrew, et al.
Published: (2025)
Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
by: Tang, Xuan, et al.
Published: (2025)
by: Tang, Xuan, et al.
Published: (2025)
Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization
by: Irie, Kaichi, et al.
Published: (2025)
by: Irie, Kaichi, et al.
Published: (2025)
A Generalized Acquisition Function for Preference-based Reward Learning
by: Ellis, Evan, et al.
Published: (2024)
by: Ellis, Evan, et al.
Published: (2024)
LLMForge: Multi-Backend Hardware-Aware Neural Architecture Search with Infinite-Head Attention for Edge Language Models
by: Jiang, Xinting, et al.
Published: (2026)
by: Jiang, Xinting, et al.
Published: (2026)
Exchangeability in Neural Network and its Application to Dynamic Pruning
by: Pu, et al.
Published: (2025)
by: Pu, et al.
Published: (2025)
A Functional Perspective on Knowledge Distillation in Neural Networks
by: Mason-Williams, Israel, et al.
Published: (2025)
by: Mason-Williams, Israel, et al.
Published: (2025)
Infinite Video Understanding
by: Zhang, Dell, et al.
Published: (2025)
by: Zhang, Dell, et al.
Published: (2025)
Comparative analysis of Realistic EMF Exposure Estimation from Low Density Sensor Network by Finite & Infinite Neural Networks
by: Mallik, Mohammed, et al.
Published: (2025)
by: Mallik, Mohammed, et al.
Published: (2025)
A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning
by: Jun, James P, et al.
Published: (2025)
by: Jun, James P, et al.
Published: (2025)
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
by: Sieber, Jerome, et al.
Published: (2024)
by: Sieber, Jerome, et al.
Published: (2024)
Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations
by: Cunegatti, Elia, et al.
Published: (2023)
by: Cunegatti, Elia, et al.
Published: (2023)
Similar Items
-
Are More Tokens Rational? Inference-Time Scaling in Language Models as Adaptive Resource Rationality
by: Hu, Zhimin, et al.
Published: (2026) -
Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning
by: Lian, Xin, et al.
Published: (2024) -
Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments
by: Gandhi, Atith, et al.
Published: (2024) -
A Distributional Analogue to the Successor Representation
by: Wiltzer, Harley, et al.
Published: (2024) -
The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis
by: Pham, Hoang, et al.
Published: (2025)