Michael DeWeese: Difference between revisions

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Here is my [http://redwood.berkeley.edu/w/images/7/76/DeWeese_cv_short.pdf short CV] and below is my publication list.  Most papers are available here as PDFs.
Here is my [http://redwood.berkeley.edu/w/images/7/76/DeWeese_cv_short.pdf short CV] and below is my publication list.  Most papers are available here as PDFs.


'''Publications:'''
*49. P.S. Sachdeva, J.A. Livezey, M.R. DeWeese. Heterogeneous synaptic weighting improves neural coding in the presence of common noise. Neural Computation, in press. (2020).
*48. M.Y.S. Fang, S. Manipatruni, C. Wierzynski, A. Khosrowshahi, M.R. DeWeese. Design of optical neural networks with component imprecisions. Optics express 27, 14009-14029. (2019).
*47. M.N. Insanally, I. Carcea, R.E. Field, C.C. Rodgers, B. DePasquale, K. Rajan, M.R. DeWeese, B.F. Albanna, R.C. Froemke. Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons. eLife 8, e42409. (2019).
*46. E.M.V. Dodds, M.R. DeWeese. On the sparse structure of natural sounds and natural images: similarities, differences, and implications for neural coding. Frontiers in computational neuroscience 13, 39. (2019).
*45. L. Kang, M.R. DeWeese. Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network. eLife 8, e46351. (2019).
*44. D. Mandal, K. Klymko, and M.R. DeWeese. Reply to Comment on ``Entropy Production and Fluctuation Theorems for Active Matter". Physical review letters 121, 139802. (2018).
*43. D. Mandal, K. Klymko, and M.R. DeWeese. Entropy Production and Fluctuation Theorems for Active Matter. Physical Review Letters 119, 258001. (2017).
*42. B. Albanna, C. Hillar, J. Sohl-Dickstein and M.R. DeWeese. Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations. Entropy 19, 427 (2017).
*41. G. Dunn, K. Shen, J.N. Belling, T.N.H. Nguyen, E. Barkovich, K. Chism, M.M. Maharbiz, M.R. DeWeese and A. Zettl. Selective Insulation of Carbon Nanotubes. Physica Status Solidi B. 00, 1700202 (2017).
*40. D. Mandal and M.R. DeWeese. [http://redwood.berkeley.edu/w/images/1/1e/Mandal_%26_DeWeese_PRE_JE_generalized_to_nonHamiltonian_dynamics_2016.pdf Nonequilibrium work energy relation for non-Hamiltonian dynamics.] Physical Review E. 93(4):042129. (2016).


'''Publications:'''
*39. P.R. Zulkowski and M.R. DeWeese. [http://redwood.berkeley.edu/w/images/f/f0/Zulkowski_DeWeese_Overdamped_Systems_PRE_2015.pdf Optimal control of overdamped systems.] Physical Review E. 92(3):032117. (2015).
*39. P.R. Zulkowski and M.R. DeWeese. [http://redwood.berkeley.edu/w/images/f/f0/Zulkowski_DeWeese_Overdamped_Systems_PRE_2015.pdf Optimal control of overdamped systems.] Physical Review E. 92(3):032117. (2015).


*38. P.R. Zulkowski and M.R. DeWeese. [[File:x.pdf]] Optimal protocols for slowly driven quantum systems. Physical Review E. 92(3):032113. (2015).
*38. P.R. Zulkowski and M.R. DeWeese. [http://redwood.berkeley.edu/w/images/3/32/Zulkowski_DeWeese_Driven_Quantum_Systems_PRE_2015.pdf Optimal protocols for slowly driven quantum systems.] Physical Review E. 92(3):032113. (2015).


*37. S.E. Marzen, M.R. DeWeese, and J.P. Crutchfield, [http://redwood.berkeley.edu/w/images/9/93/Marzen_DeWeese_Crutchfield_time_rez_dep_info_spiking_neurons_2015.pdf Time Resolution Dependence of Information Measures for Spiking Neurons: Scaling and Universality.] Frontiers in Computational Neuroscience. 9:105. (2015).
*37. S.E. Marzen, M.R. DeWeese, and J.P. Crutchfield, [http://redwood.berkeley.edu/w/images/9/93/Marzen_DeWeese_Crutchfield_time_rez_dep_info_spiking_neurons_2015.pdf Time Resolution Dependence of Information Measures for Spiking Neurons: Scaling and Universality.] Frontiers in Computational Neuroscience. 9:105. (2015).

Latest revision as of 09:22, 4 March 2020

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

Publications:

  • 49. P.S. Sachdeva, J.A. Livezey, M.R. DeWeese. Heterogeneous synaptic weighting improves neural coding in the presence of common noise. Neural Computation, in press. (2020).
  • 48. M.Y.S. Fang, S. Manipatruni, C. Wierzynski, A. Khosrowshahi, M.R. DeWeese. Design of optical neural networks with component imprecisions. Optics express 27, 14009-14029. (2019).
  • 47. M.N. Insanally, I. Carcea, R.E. Field, C.C. Rodgers, B. DePasquale, K. Rajan, M.R. DeWeese, B.F. Albanna, R.C. Froemke. Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons. eLife 8, e42409. (2019).
  • 46. E.M.V. Dodds, M.R. DeWeese. On the sparse structure of natural sounds and natural images: similarities, differences, and implications for neural coding. Frontiers in computational neuroscience 13, 39. (2019).
  • 45. L. Kang, M.R. DeWeese. Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network. eLife 8, e46351. (2019).
  • 44. D. Mandal, K. Klymko, and M.R. DeWeese. Reply to Comment on ``Entropy Production and Fluctuation Theorems for Active Matter". Physical review letters 121, 139802. (2018).
  • 43. D. Mandal, K. Klymko, and M.R. DeWeese. Entropy Production and Fluctuation Theorems for Active Matter. Physical Review Letters 119, 258001. (2017).
  • 42. B. Albanna, C. Hillar, J. Sohl-Dickstein and M.R. DeWeese. Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations. Entropy 19, 427 (2017).
  • 41. G. Dunn, K. Shen, J.N. Belling, T.N.H. Nguyen, E. Barkovich, K. Chism, M.M. Maharbiz, M.R. DeWeese and A. Zettl. Selective Insulation of Carbon Nanotubes. Physica Status Solidi B. 00, 1700202 (2017).
  • 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).