Michael DeWeese: Difference between revisions

From RedwoodCenter
Jump to navigationJump to search
No edit summary
No edit summary
Line 39: Line 39:
*28.  P. King, J. Zylberberg, and M.R. DeWeese.  [https://redwood.berkeley.edu/w/images/2/29/King_Zylberberg_DeWeese_E_I_Net_Model_of_V1_JNeurosci_2013.pdf Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1.] Journal of Neuroscience 33(13):5475–85 (2013).
*28.  P. King, J. Zylberberg, and M.R. DeWeese.  [https://redwood.berkeley.edu/w/images/2/29/King_Zylberberg_DeWeese_E_I_Net_Model_of_V1_JNeurosci_2013.pdf Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1.] Journal of Neuroscience 33(13):5475–85 (2013).


*27.  J. Zylberberg, D. Pfau, and M.R. DeWeese.  [https://redwood.berkeley.edu/w/images/e/ee/Zylberberg_Pfau_DeWeese_PRE_2012_reprint.pdf Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments.] Physical Review E. 86:066112 (2012).
*27.  J. Zylberberg, D. Pfau, and M.R. DeWeese.  [https://redwood.berkeley.edu/w/images/e/ee/Zylberberg_Pfau_DeWeese_PRE_2012_reprint.pdf Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments.] Physical Review E. 86(6):066112 (2012).


*26.  P.R. Zulkowski, D.A. Sivak, G.E. Crooks, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/c/cb/Zulkowski_Sivak_Crooks_DeWeese_PRE_2012_reprint.pdf The geometry of thermodynamic control.] Physical Review E. 86(4 Pt 1):041148 (2012).
*26.  P.R. Zulkowski, D.A. Sivak, G.E. Crooks, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/c/cb/Zulkowski_Sivak_Crooks_DeWeese_PRE_2012_reprint.pdf The geometry of thermodynamic control.] Physical Review E. 86(4):041148 (2012).


*25.  N. Carlson, V.L. Ming, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/4/4b/Carlson_Ming_DeWeese_Sparse_speech_ICC_PLoS_CB_2012_reprint.pdf Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus.] Public Library of Science Computational Biology. 7(10):e1002250 (2012).
*25.  N. Carlson, V.L. Ming, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/4/4b/Carlson_Ming_DeWeese_Sparse_speech_ICC_PLoS_CB_2012_reprint.pdf Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus.] Public Library of Science Computational Biology. 7(10):e1002250 (2012).

Revision as of 03:26, 31 December 2013

Here is my short CV and below is my publication list including some preprints. Most papers are available here as PDFs.

Selected manuscripts in preparation:

  • k. V. Carels and M.R. DeWeese. A comparison of multi- and single-unit spectrotemporal receptive fields in the primary auditory cortex. (in preparation)
  • j. P.R. Zulkowski and M.R. DeWeese. Optimal entropy production. (in preparation)
  • h. M. Leonard and M.R. DeWeese. A subpopulation of neurons in prefrontal cortex encode recent actions in a working memory task but only during uncued trials. (in preparation)
  • g. N. Carlson, V.L. Ming, and M.R. DeWeese. Probe stimuli affect receptive field estimation of model auditory neurons optimized to represent speech efficiently. (in preparation)
  • e. S. Corinaldi and M.R. DeWeese. A network model of task switching optimized to minimize errors predicts several counterintuitive features of human behavioral data. (in preparation)

Submitted manuscripts:

All publications:

  • 23. J. Sohl-Dickstein, P. Battaglino, and M.R. DeWeese. Minimum Probability Flow Learning. Proceedings of the 28th International Conference on Machine Learning (Bellevue, WA) (2011).
  • 11. M.R. DeWeese and A.M. Zador. Binary coding in auditory cortex. In Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA, Vol. 15, 101 (2003).
  • 5. M.R. DeWeese. Optimization principles for the neural code. Network 7, 325-331 (1996).