NeurIPS 2024 Past Neuroscience
The First Workshop on NeuroAI @ NeurIPS2024
NeuroAI @ NeurIPS 2024
- Submission deadline
- Sep 10, 2024, 13:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (43)
Fetched from OpenReview (v2) on 2026-06-10.
-
A call for intrinsic learning
-
A Hopfield network model of neuromodulatory arousal state
-
A Walsh Hadamard Derived Linear Vector Symbolic Architecture
-
Asynchronous Hebbian/anti-Hebbian networks
-
Beyond Directed Acyclic Computation Graph with Cyclic Neural Network
-
Brain in the Dark: Design Principles for Neuromimetic Inference under the Free Energy Principle
-
Common visual learning constraints in transformers and newborn brains: Evidence from line drawings
-
Decoupling the Contributions of Spatio-Temporal Coding: From ANNs to SNNs
-
Doing More with Less: Computational Role of Information Structure in Neural Networks based on Entropy Maximization
-
Dyadic Learning in Recurrent and Feedforward Models
-
Dynamics Based Neural Encoding with Inter-Intra Region Connectivity
-
Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building
-
Hierarchical Control of Reaching Movements Via Compositional Gain Modulation
-
Homeostasis-aware Direct Spike Encoding for Deep Spiking Neural Networks
-
How do Active Dendrite Networks Mitigate Catastrophic Forgetting?
-
Improving out-of-distribution generalization by mimicking the human visual diet.
-
Invariant Spatiotemporal Representation Learning for Cross-patient Seizure Classification
-
Learning Bayes-Optimal Representation in Partially Observable Environments via Meta-Reinforcement Learning with Predictive Coding
-
Liquid Resistance Liquid Capacitance Networks
-
Multiple temporal credit assignment rules achieve comparable neural data similarity
-
Natural Language-guided Neural Encoding Benchmark for Vision
-
Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shift
-
NetFormer: An interpretable model for recovering identity and structure in neural population dynamics
-
Neural Embedding Ranks: Aligning 3D latent dynamics with movement for long-term decoding
-
Neuron-Astrocyte Associative Memory
-
Not so griddy: Internal representations of RNNs path integrating more than one agent
-
Parallel Decision-Making yields Disentangled World Models: Impact and Implications
-
Partial observation can induce mechanistic mismatches in data-constrained RNNs
-
Path Divergence Objective: Boundedly-Rational Decision Making in Partially Observable Environments
-
Population Transformer: Learning Population-level Representations of Intracranial Activity
-
Predictive Coding Graphs are a Superset of Feedforward Neural Networks
-
Predictive Learning Induces Probabilistic Cognitive Maps
-
Proliferation of cosine-tuning in both artificial spiking and cortical neural networks during learning
-
Prospective Learning: Learning for a Dynamic Future
-
RNN Replay: Leakage and Underdamped Dynamics
-
SynapsNet: Enhancing Neuronal Population Dynamics Modeling via Learning Functional Connectivity
-
The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning
-
The Role of Cortical Varibility in Supporting Few-shot Generalization: Theory and Empirical Evidence
-
Towards zero-shot adaptation of predictive models of neurons encoding posterior probability
-
Uncovering Neural Encoding Variability with Infinite Gaussian Process Factor Analysis
-
Value of Information and Reward Specification in Active Inference and POMDPs
-
What should a neuron aim for? Designing local objective functions based on information theory
-
Why learn if you can infer? Robot arm control with Hierarchical Active Inference