Alex Lamb
According to our database1,
Alex Lamb
authored at least 60 papers
between 2012 and 2024.
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Bibliography
2024
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models.
Trans. Mach. Learn. Res., 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Neural Networks, 2022
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy.
Neural Networks, 2022
CoRR, 2022
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning.
CoRR, 2022
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information.
CoRR, 2022
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback.
CoRR, 2022
CoRR, 2022
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning.
CoRR, 2022
CoRR, 2022
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments.
Proceedings of the 9th International Conference on Learning Representations, 2021
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
SN Comput. Sci., 2020
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems.
CoRR, 2020
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Eleventh International Conference on Computational Creativity, 2020
2019
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning.
CoRR, 2019
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy.
CoRR, 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Deep Generative Models for Highly Structured Data, 2019
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy.
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019
2018
CoRR, 2018
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations.
CoRR, 2018
2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 5th International Conference on Learning Representations, 2017
2016
CoRR, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
2015
2013
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013
2012
Proceedings of the Information Retrieval and Knowledge Discovery in Biomedical Text, 2012