CUED Publications database

Items where Division is "Div F > Computational and Biological Learning" and Year is 2018

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Number of items: 74.

A

Adel, T and Ghahramani, Z and Wcller, A (2018) Discovering interpretable representations for both deep generative and discriminative models. In: UNSPECIFIED pp. 86-101..

Adel, T and Ghahramani, Z and Weller, A (2018) Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. In: UNSPECIFIED pp. 50-59..

Athey, S and Blei, D and Donnelly, R and Ruiz, F and Schmidt, T (2018) Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data. In: AEA PAPERS AND PROCEEDINGS, -- to -- pp. 64-67..

B

Bernacchia, A and Lengyel, M and Hennequin, G (2018) Exact natural gradient in deep linear networks and application to the nonlinear case. In: Neural Information Processing Systems, 2018-12-2 to 2018-12-8, Montreal pp. 5941-5950.. (Unpublished)

Bhatnagar, S and Alexandrova, A and Avin, S and Cave, S and Cheke, L and Crosby, M and Feyereisl, J and Halina, M and Loe, BS and Ó hÉigeartaigh, S and Martínez-Plumed, F and Price, H and Shevlin, H and Weller, A and Winfield, A and Hernández-Orallo, J (2018) Mapping Intelligence: Requirements and Possibilities. In: Studies in Applied Philosophy, Epistemology and Rational Ethics. UNSPECIFIED, pp. 117-135.

Budzianowski, PF and Casanueva, I and Tseng, B-H and Gasic, M (2018) Towards end-to-end multi-domain dialogue modelling. Technical Report. UNSPECIFIED.

C

Calliess, JM and Roberts, S and Rasmussen, CE and Maciejowski, J (2018) Nonlinear Set Membership Regression with Adaptive Hyper-Parameter Estimation for Online Learning and Control. In: European Control Conference, 2018-6-12 to 2018-6-15, Limassol pp. 3167-3172..

D

De Matthews, AGG and Hron, J and Rowland, M and Turner, RE and Ghahramani, Z (2018) Gaussian process behaviour in wide deep neural networks. In: 6th International Conference on Learning Representations, 2018-4-30 to --.

Depeweg, S and Hernandez-Lobato, JM and Doshi-Velez, F and Udluft, S (2018) Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning. 35th International Conference on Machine Learning, ICML 2018, 3. pp. 1920-1934.

Depeweg, S and Hernández-Lobato, JM and Udluft, S and Runkler, T (2018) Sensitivity analysis for predictive uncertainty in Bayesian neural networks. ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. pp. 279-284.

E

Echeveste, R and Lengyel, M (2018) The Redemption of Noise: Inference with Neural Populations. Trends in Neurosciences, 41. pp. 767-770. ISSN 0166-2236

Elfwing, S and Seymour, B (2018) Parallel reward and punishment control in humans and robots: Safe reinforcement learning using the MaxPain algorithm. 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017, 2018-J. pp. 140-147.

G

Gallivan, J and Chapman, C and Wolpert, DM and Flanagan, JR (2018) Decision-making in sensorimotor control. Nature Reviews Neuroscience, 19. pp. 519-534. ISSN 1471-0048 (Unpublished)

Ge, H and Xu, K and Ghahramani, Z (2018) Turing: A language for flexible probabilistic inference. In: 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), 2018-4-9 to 2018-4-11, Playa Blanca, Lanzarote, Canary Islands pp. 1682-1690..

Ge, H and Xu, K and Ghahramani, Z (2018) Turing: A language for flexible probabilistic inference. In: UNSPECIFIED.

Ge, H and Xu, K and Ghahramani, Z (2018) Turing: Composable inference for probabilistic programming. In: UNSPECIFIED pp. 1682-1690..

Gómez-Bombarelli, R and Wei, JN and Duvenaud, D and Hernández-Lobato, JM and Sánchez-Lengeling, B and Sheberla, D and Aguilera-Iparraguirre, J and Hirzel, TD and Adams, RP and Aspuru-Guzik, A (2018) Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules. ACS Central Science, 4. pp. 268-276. ISSN 2374-7943

H

Havasi, M and Hernández-Lobato, JM and Murillo-Fuentes, JJ (2018) Inference in deep Gaussian processes using stochastic gradient hamiltonian Monte Carlo. Advances in Neural Information Processing Systems, 2018-D. pp. 7506-7516. ISSN 1049-5258

Heald, JB and Franklin, DW and Wolpert, DM (2018) Increasing muscle co-contraction speeds up internal model acquisition during dynamic motor learning. Scientific Reports, 8. 16355-.

Heald, JB and Ingram, JN and Flanagan, JR and Wolpert, DM (2018) Multiple motor memories are learned to control different points on a tool. Nature Human Behaviour, 2. pp. 300-311. ISSN 2397-3374

Hennequin, G and Ahmadian, Y and Rubin, DB and Lengyel, M and Miller, KD (2018) The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability. Neuron, 98. 846-860.e5. ISSN 0896-6273

Hron, J and De G Matthews, AG and Ghahramani, Z (2018) Variational Bayesian dropout: Pitfalls and fixes. 35th International Conference on Machine Learning, ICML 2018, 5. pp. 3199-3219.

J

Janz, D and Van Der Westhuizen, J and Paige, B and Kusner, MJ and Hernández-Lobato, JM (2018) Learning a generative model for validity in complex discrete structures. 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings.

K

Kao, T-C and Hennequin, G (2018) Null Ain't Dull: New Perspectives on Motor Cortex. Trends Cogn Sci, 22. pp. 1069-1071. ISSN 1364-6613

Keshavarzi, M and Goehring, T and Zakis, J and Turner, RE and Moore, BCJ (2018) Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality. Trends in Hearing, 22. 2331216518770964-.

L

Law, S and Paige, B and Russell, C (2018) Take a Look Around: Using Street View and Satellite Images to Estimate House Prices. arXiv preprint arXiv:1807.07155.

Liao, Q and Kulkarni, Y and Sengupta, U and Petrović, D and Mulholland, AJ and van der Kamp, MW and Strodel, B and Kamerlin, SCL (2018) Loop Motion in Triosephosphate Isomerase Is Not a Simple Open and Shut Case. J Am Chem Soc, 140. pp. 15889-15903. ISSN 0002-7863

M

Mancini, F and Pepe, A and Bernacchia, A and Di Stefano, G and Mouraux, A and Iannetti, GD (2018) Characterizing the short-term habituation of event-related evoked potentials. eNeuro, 5.

Mano, H and Kotecha, G and Leibnitz, K and Matsubara, T and Sprenger, C and Nakae, A and Shenker, N and Shibata, M and Voon, V and Yoshida, W and Lee, M and Yanagida, T and Kawato, M and Rosa, MJ and Seymour, B (2018) Classification and characterisation of brain network changes in chronic back pain: A multicenter study. Wellcome Open Research. ISSN 2398-502X

Mattar, M and Carter, M and Zebrowitz, M and Thompson-Schill, S and Aguirre, G (2018) Individual differences in response precision correlate with adaptation bias.

Mattar, MG and Daw, ND (2018) Prioritized memory access explains planning and hippocampal replay. Nat Neurosci, 21. pp. 1609-1617.

Mattar, MG and Olkkonen, M and Epstein, RA and Aguirre, GK (2018) Adaptation decorrelates shape representations. Nat Commun, 9. 3812-.

Morris, L and Sprenger, C and Koda, K and de la Mora, D and Yamada, T and Mano, H and Kashiwagi, Y and Yoshioka, Y and Morioka, Y and Seymour, BJ (2018) Anterior cingulate cortex connectivity is associated with suppression of behavior in a rat model of chronic pain. Brain and Neuroscience Advances, 2. pp. 1-7. ISSN 2398-2128 (Unpublished)

Mukuta, Y and Kimura, A and Adrian, DB and Ghahramani, Z (2018) Weakly supervised collective feature learning from curated media. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. pp. 7260-7267.

N

Norbury, A and Robbins, TW and Seymour, B (2018) Aversive Value Generalization During Human Avoidance Learning Predicts Anxiety. In: UNSPECIFIED S244-S245..

Norbury, A and Robbins, TW and Seymour, B (2018) Value generalization in human avoidance learning. eLife, 7.

Norbury, A and Robbins, TW and Seymour, B (2018) Value generalization in human avoidance learning. eLife, 7.

Norbury, AE and Seymour, B (2018) Response heterogeneity: Challenges for personalised medicine and big data approaches in psychiatry and chronic pain. F1000Research, 7. p. 55. ISSN 2046-1402

P

Parmas, P and Rasmussen, CE and Peters, J and Doya, K (2018) PIPPS: Flexible model-based policy search robust to the curse of chaos. In: International Conference on Machine Learning, 2018-7-10 to 2018-7-15 pp. 6463-6472..

Penfold, CA and Sybirna, A and Reid, JE and Huang, Y and Wernisch, L and Ghahramani, Z and Grant, M and Surani, MA (2018) Branch-recombinant Gaussian processes for analysis of perturbations in biological time series. Bioinformatics, 34. i1005-i1013. ISSN 1367-4803

Piccolo, L and Libera, FD and Bonarini, A and Seymour, B and Ishiguro, H (2018) Pain and self-preservation in autonomous robots: From neurobiological models to psychiatric disease. 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017, 2018-J. pp. 263-270.

R

Roth, W and Peharz, R and Tschiatschek, S and Pernkopf, F (2018) Hybrid generative-discriminative training of Gaussian mixture models. Pattern Recognition Letters, 112. pp. 131-137. ISSN 0167-8655

Rowland, M and Choromanski, K and Chalus, F and Pacchiano, A and Sarlós, T and Turner, RE and Weller, A (2018) Geometrically coupled monte carlo sampling. In: UNSPECIFIED pp. 195-206..

Ruiz, FJR and Titsias, MK and Dieng, AB and Blei, DM (2018) Augment and reduce: Stochastic inference for large Categorical distributions. 35th International Conference on Machine Learning, ICML 2018, 10. pp. 6997-7006.

S

Sadabadi, MS and Shafiee, Q and Karimi, A (2018) Plug-and-Play Robust Voltage Control of DC Microgrids. IEEE Transactions on Smart Grid, 9. pp. 6886-6896. ISSN 1949-3053

Sadeghi, M and Ingram, JN and Wolpert, DM (2018) Adaptive coupling influences generalization of sensorimotor learning. PLoS ONE, 13. e0207482-.

Schlittenlacher, J and Turner, RE and Moore, BCJ (2018) A Hearing-Model-Based Active-Learning Test for the Determination of Dead Regions. Trends in Hearing, 22. 2331216518788215-. ISSN 2331-2165

Sengupta, U and Strodel, B (2018) Markov models for the elucidation of allosteric regulation. Philos Trans R Soc Lond B Biol Sci, 373. p. 20170178. ISSN 0962-8436

Seymour, B and Mano, H and Kotecha, G and Leibnitz, K and Matsubara, T and Nakae, A and Shenker, N and Shibata, M and Voon, V and Yoshida, W and Lee, M and Yanagida, T and Kawato, M and Rosa, MJ (2018) Classification and characterisation of brain network changes in chronic back pain: A multicenter study [version 1; referees: 3 approved]. Wellcome Open Research, 3. 19-. ISSN 2398-502X

Sheahan, HR and Ingram, JN and Žalalytė, GM and Wolpert, DM (2018) Imagery of movements immediately following performance allows learning of motor skills that interfere. Scientific Reports, 8. 14330-.

Stroud, J and Hennequin, G and Porter, M and Vogels, T (2018) Motor primitives in space and time via targeted gain modulation in cortical networks.

Stroud, JP and Porter, MA and Hennequin, G and Vogels, TP (2018) Motor primitives in space and time via targeted gain modulation in cortical networks. Nat Neurosci, 21. pp. 1774-1783. ISSN 1097-6256

Stroud, JP and Vogels, TP (2018) Cortical Signal Propagation: Balance, Amplify, Transmit. Neuron, 98. pp. 8-9.

T

Tegho, C and Budzianowski, P and Gasic, M (2018) Benchmarking Uncertainty Estimates with Deep Reinforcement Learning for Dialogue Policy Optimisation. In: UNSPECIFIED pp. 6069-6073..

Therrien, AS and Wolpert, DM and Bastian, AJ (2018) Increasing motor noise impairs reinforcement learning in healthy individuals. eNeuro, 5.

Thicker, G and Bhupatiraju, S and Gu, S and Turner, RE and Ghahramani, Z and Levine, S (2018) The mirage of action-dependent baselines in reinforcement learning. In: UNSPECIFIED pp. 7985-7994..

Tourigny, D and Kaiser Abdul Karim, M and Echeveste, R and Kotter, M and O’Neill, J (2018) Energetic substrate availability regulates synchronous activity in an excitatory neural network.

Trapp, P and Echeveste, R and Gros, C (2018) E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks. Scientific Reports, 8. 8939-.

Tucker, G and Bhupatiraju, S and Gu, S and Turner, RE and Ghahramani, Z and Levine, S (2018) The Mirage of Action-Dependent Baselines in Reinforcement Learning. In: ICML 2018: 35th International Conference on Machine Learning, 2018-7-10 to 2018-7-15, Stockholm, Sweden pp. 5015-5024..

U

Ujfalussy, BB and Makara, JK and Lengyel, M and Branco, T (2018) Global and Multiplexed Dendritic Computations under In Vivo-like Conditions. Neuron, 100. 579-592.e5. ISSN 0896-6273

V

Vulic, I and Glavaš, G and Mrkšić, N and Korhonen, A (2018) Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources. In: Proceedings of the 16th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), 2018-6-1 to 2018-4-6, New Orleans, LA, USA.

Vulic, I and Mrkšić, N (2018) Specialising Word Vectors for Lexical Entailment. In: 16th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), 2018-6-1 to 2018-6-6, New Orleans, LA, USA pp. 1134-1144..

van de Meent, J-W and Paige, B and Yang, H and Wood, F (2018) An Introduction to Probabilistic Programming. arXiv preprint arXiv:1809.10756.

W

Wang, O and Lee, S and O'Doherty, J and Seymour, BJ and Yoshida, W (2018) Model-based and model-free pain avoidance learning. Brain and Neuroscience Advances, 2. 2398212818772964-. ISSN 2398-2128 (Unpublished)

Weisz, G and Budzianowski, P and Su, PH and Gasic, M (2018) Sample Efficient Deep Reinforcement Learning for Dialogue Systems with Large Action Spaces. IEEE/ACM Transactions on Audio Speech and Language Processing, 26. pp. 2083-2097. ISSN 2329-9290

Wolpe, N and Zhang, J and Nombela, C and Ingram, JN and Wolpert, DM and Cam-CAN, and Rowe, JB (2018) Publisher Correction: Sensory attenuation in Parkinson's disease is related to disease severity and dopamine dose. Sci Rep, 8. p. 17429.

Wolpe, N and Zhang, J and Nombela, C and Ingram, JN and Wolpert, DM and Rowe, JB and Tyler, LK and Brayne, C and Bullmore, ET and Calder, AC and Cusack, R and Dalgleish, T and Duncan, J and Matthews, FE and Marslen-Wilson, WD and Shafto, MA and Cheung, T and Geerligs, L and McCarrey, A and Mustafa, A and Price, D and Samu, D and Treder, M and Tsvetanov, KA and van Belle, J and Williams, N and Bates, L and Gadie, A and Gerbase, S and Georgieva, S and Hanley, C and Parkin, B and Troy, D and Auer, T and Correia, M and Gao, L and Green, E and Henriques, R and Allen, J and Amery, G and Amunts, L and Barcroft, A and Castle, A and Dias, C and Dowrick, J and Fair, M and Fisher, H and Goulding, A and Grewal, A and Hale, G and Hilton, A and Johnson, F and Johnston, P and Kavanagh-Williamson, T and Kwasniewska, M and McMinn, A and Norman, K and Penrose, J and Roby, F and Rowland, D and Sargeant, J and Squire, M and Stevens, B and Stoddart, A and Stone, C and Thompson, T and Yazlik, O and Dan Barnes, and Dixon, M and Hillman, J and Mitchell, J and Villis, L (2018) Sensory attenuation in Parkinson’s disease is related to disease severity and dopamine dose. Scientific Reports, 8. 15643-. ISSN 2045-2322

Y

Yamashita, M and Yoshihara, Y and Hashimoto, R and Yahata, N and Ichikawa, N and Sakai, Y and Yamada, T and Matsukawa, N and Okada, G and Tanaka, SC and Kasai, K and Kato, N and Okamoto, Y and Seymour, B and Takahashi, H and Kawato, M and Imamizu, H (2018) A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity. eLife, 7.

Yanagisawa, T and Fukuma, R and Seymour, B and Hosomi, K and Kishima, H and Shimizu, T and Yokoi, H and Hirata, M and Yoshimine, T and Kamitani, Y and Saitoh, Y (2018) MEG–BMI to control phantom limb pain. Neurologia Medico-Chirurgica, 58. pp. 327-333. ISSN 0470-8105

Z

Zhang, S and Mano, H and Lee, M and Yoshida, W and Kawato, M and Robbins, TW and Seymour, B (2018) The control of tonic pain by active relief learning. eLife, 7.

Zhang, S and Yoshida, W and Mano, H and Yanagisawa, T and Shibata, K and Kawato, M and Seymour, B (2018) Endogenous controllability of closed-loop brain-machine interfaces for pain.

Zylberberg, A and Wolpert, D and Shadlen, M (2018) Counterfactual reasoning underlies the learning of priors in decision making. Neuron. ISSN 0896-6273

Zylberberg, A and Wolpert, DM and Shadlen, MN (2018) Counterfactual Reasoning Underlies the Learning of Priors in Decision Making. Neuron, 99. 1083-1097.e6. ISSN 0896-6273

Ś

Ścibior, AM and Kammar, O and Ghahramani, Z (2018) Functional Programming for Modular Bayesian Inference. Proceedings of the ACM on Programming Languages, 2. pp. 1-29.

This list was generated on Mon Aug 3 16:02:41 2020 BST.