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如需批Geoffrey E. Hinton's Publications

in Reverse Chronological Order

2022  2021  2020  2019  2018  2017  2016  2015  2014  2013  2012  2011  2010  2009  2008  2007  2006  2005  2004  2003  2002  2001  2000  1999  1998  1997  1996  1995  1994  1993  1992  1991  1990  1989  1988  1987  1986  1985  1984  1983-1976

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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