% Key papers for Recurrent circuit models of inference (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_infogail_56385,
  title = {{InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9163},
}

@inproceedings{neurips2017_reconstructing_56613,
  title = {{Reconstructing perceived faces from brain activations with deep adversarial neural decoding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9204},
}

@inproceedings{neurips2017_neural_56509,
  title = {{Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9413},
}

@inproceedings{neurips2020_reverse_60718,
  title = {{Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18982},
}

@inproceedings{neurips2018_manifold_57356,
  title = {{Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11682},
}

@inproceedings{neurips2017_quantifying_56603,
  title = {{Quantifying how much sensory information in a neural code is relevant for behavior}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9151},
}

@inproceedings{neurips2016_a_55526,
  title = {{A Bayesian method for reducing bias in neural representational similarity analysis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6896},
}

@inproceedings{neurips2018_efficient_57089,
  title = {{Efficient inference for time-varying behavior during learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11555},
}

@inproceedings{neurips2018_generalisation_57159,
  title = {{Generalisation of structural knowledge in the hippocampal-entorhinal system}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11811},
}

@inproceedings{neurips2017_model_56481,
  title = {{Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9132},
}

@inproceedings{neurips2018_learning_57303,
  title = {{Learning a latent manifold of odor representations from neural responses in piriform cortex}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11525},
}

@inproceedings{neurips2019_better_57947,
  title = {{Better Transfer Learning with Inferred Successor Maps}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14572},
}

@inproceedings{neurips2017_training_56738,
  title = {{Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9230},
}

@inproceedings{neurips2020_efficient_59776,
  title = {{Efficient estimation of neural tuning during naturalistic behavior}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19021},
}

@inproceedings{aaai2018_the_100576,
  title = {{The Structural Affinity Method for Solving the Raven's Progressive Matrices Test for Intelligence}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11323},
}

@inproceedings{iclr2023_disentanglement_32169,
  title = {{Disentanglement with Biological Constraints: A Theory of Functional Cell Types}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10981},
}

@inproceedings{neurips2021_latent_62636,
  title = {{Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27114},
}

@inproceedings{neurips2022_distinguishing_64018,
  title = {{Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52869},
}

@inproceedings{neurips2021_a_61382,
  title = {{A universal probabilistic spike count model reveals ongoing modulation of neural variability}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26252},
}

@inproceedings{neurips2021_impression_61998,
  title = {{Impression learning: Online representation learning with synaptic plasticity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28033},
}

@inproceedings{neurips2024_model_74086,
  title = {{Model Based Inference of Synaptic Plasticity Rules}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93446},
}

@inproceedings{neurips2025_from_80462,
  title = {{From Synapses to Dynamics: Obtaining Function from Structure in a Connectome Constrained Model of the Head Direction Circuit}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=zn4F6os6cq},
}

@inproceedings{neurips2024_active_73811,
  title = {{Active learning of neural population dynamics using two-photon holographic optogenetics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93697},
}

@inproceedings{neurips2025_bridging_74939,
  title = {{Bridging Scales: Spectral Theory Reveals How Local Connectivity Rules Sculpt Global Neural Dynamics in Spatially Extended Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2hzyfArJi6},
}

@inproceedings{iclr2024_sufficient_34434,
  title = {{Sufficient conditions for offline reactivation in recurrent neural networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18641},
}

@inproceedings{iclr2024_complex_34457,
  title = {{Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18617},
}

@inproceedings{iclr2024_learning_34692,
  title = {{Learning dynamic representations of the functional connectome in neurobiological networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18382},
}

@inproceedings{icml2025_cogreact_47092,
  title = {{CogReact: A Reinforced Framework to Model Human Cognitive Reaction Modulated by Dynamic Intervention}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45494},
}

@inproceedings{icml2026_structure_50251,
  title = {{Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=AYXgo5FjYz},
}

@inproceedings{neurips2024_the_72455,
  title = {{The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94903},
}

@inproceedings{neurips2024_nonlinear_73859,
  title = {{Nonlinear dynamics of localization in neural receptive fields}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93650},
}

@inproceedings{neurips2024_shaping_73907,
  title = {{Shaping the distribution of neural responses with interneurons in a recurrent circuit model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93604},
}

@inproceedings{neurips2024_continuous_74635,
  title = {{Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/92957},
}

@inproceedings{neurips2025_inference_74946,
  title = {{Inference with correlated priors using sisters cells}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2n6fd8QlEC},
}

@inproceedings{neurips2025_neurons_77779,
  title = {{Neurons as Detectors of Coherent Sets in Sensory Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=XTHI90js2e},
}

@inproceedings{neurips2025_poco_77807,
  title = {{POCO: Scalable Neural Forecasting through Population Conditioning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Xma2G1ak3H},
}

@inproceedings{iclr2025_shared_84162,
  title = {{Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27666},
}

@inproceedings{iclr2026_setting_86213,
  title = {{Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=NGThArVrD3},
}

@inproceedings{iclr2026_tavae_87884,
  title = {{TAVAE: A VAE with Adaptable Priors Explains Contextual Modulation in the Visual Cortex}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=gdafM5zp1h},
}

@inproceedings{neurips2026_decomposing_89621,
  title = {{Decomposing the modulation of interactions between neuronal populations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152282},
}