如需批Geoffrey E. Hinton's Publications

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2022	Hinton, G. E. The Forward-Forward Algorithm: Some Preliminary Investigations [pdf]
2022	Chen, T., Zhang, R., & Hinton, G. Analog bits: Generating discrete data using diffusion models with self-conditioning arXiv preprint arXiv:2208.04202 [pdf]
2022	Ren, M., Kornblith, S., Liao, R., & Hinton, G. Scaling Forward Gradient With Local Losses arXiv preprint arXiv:2210.03310 [pdf]
2022	Chen, T., Saxena, S., Li, L., Lin, T. Y., Fleet, D. J., & Hinton, G. A unified sequence interface for vision tasks arXiv preprint arXiv:2206.07669 [pdf]
2022	Chen, T., Li, L., Saxena, S., Hinton, G., & Fleet, D. J. A generalist framework for panoptic segmentation of images and videos arXiv preprint arXiv:2210.06366 [pdf]
2022	Liao, R., Kornblith, S., Ren, M., Fleet, D. J., & Hinton, G. Gaussian-Bernoulli RBMs Without Tears arXiv preprint arXiv:2210.10318 [pdf]
2022	Culp, L., Sabour, S., & Hinton, G. E. Testing GLOM's ability to infer wholes from ambiguous parts arXiv preprint arXiv: 2211.16564 [pdf]
2021	Hinton, G. E. How to represent part-whole hierarchies in a neural network [pdf]
2021	Agarwal, R., Melnick, L., Frosst, N., Zhang, X., Lengerich, B., Caruana, R., & Hinton, G. E. Neural additive models:Interpretable machine learning with neural nets Advances in Neural Information Processing Systems, 34, 4699-4711. [pdf]
2021	Bengio, Y., Lecun, Y., & Hinton, G. Deep learning for AI Communications of the ACM, 64(7), 58-65. [pdf]
2021	Sun, W., Tagliasacchi, A., Deng, B., Sabour, S., Yazdani, S., Hinton, G. E., Yi, K. M. Canonical Capsules: Unsupervised Capsules in Canonical Pose arXiv preprint arXiv:2012.04718 [pdf]
2021	Sabour, S., Tagliasacchi, A., Yazdani, S., Hinton, G. E., Fleet, D. J. Unsupervised part representation by Flow Capsules arXiv preprint arXiv:2011.13920 [pdf]
2020	Deng, B., Lewis, J. P., Jeruzalski, T., Pons-Moll, G., Hinton, G. E., Norouzi, M., Tagliasacchi, A. NASA: Neural Articulated Shape Approximation ECCV [pdf]
2020	Müller, R., Kornblith, S., Hinton, G. E. Subclass distillation arXiv preprint arXiv:2002.03936 [pdf]
2020	Chen, T., Kornblith, S., Swersky, K., Norouzi, M., and Hinton, G. E. Big Self-Supervised Models are Strong Semi-Supervised Learners 34th Conference on Neural Information Processing Systems (NeurIPS 2020) [pdf]
2020	Chen, T., Kornblith, S., Norouzi, M., and Hinton, G. E. A Simple Framework for Contrastive Learning of Visual Representations Proceedings of the 37th International Conference on Machine Learning. Eds. Hal Daume III and Aarti Singh, pp 1597--1607. [pdf]
2020	Lillicrap, T. P., Santoro, A., Marris, C. J,. Akerman, C., and Hinton, G. E. Backpropagation and the Brain Nature Reviews Neuroscience volume 21, pp 335--346. [pdf]
2020	Qin, Y., Frosst, N., Sabour, S., Raffel, C., Cottrell, C. and Hinton, G. Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions ICLR-2020 [pdf]
2019	Kosiorek, A. R., Sabour, S., Teh, Y. W. and Hinton, G. E. Stacked Capsule Autoencoders Advances in Neural Information Processing Systems 32 [pdf]
2019	Zhang, M., Lucas, J., Ba, J., and Hinton, G. E. Lookahead Optimizer: k steps forward, 1 step back Advances in Neural Information Processing Systems 32 [pdf]
2019	Müller, R., Kornblith, S. and Hinton G. When Does Label Smoothing Help? Advances in Neural Information Processing Systems 32 [pdf]
2019	Deng, B., Kornblith, S. and Hinton, G. (2019) Cerberus: A multi-headed derenderer 3D Scene Understanding Workshop, CVPR 2019 [pdf]
2019	Deng, B., Genova, K., Yazdani, S., Bouaziz, S., Hinton, G. and Tagliasacchi, A. (2019) Cvxnet: Learnable convex decomposition Perception as Generative Reasoning Workshop, NeurIPS 2019 [pdf]
2019	Kornblith, S., Norouzi, M., Lee, H. and Hinton, G. Similarity of neural network representations revisited

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