Travelled to:1 × France
2 × Canada
2 × China
Collaborated with:D.J.Rezende M.Wiering C.Blundell K.Gregor I.Danihelka S.Mohamed J.Cornebise K.Kavukcuoglu Y.Sun T.Schaul J.Schmidhuber A.Graves A.Mnih D.Silver G.Lever N.Heess T.Degris M.A.Riedmiller
Talks about:network (3) stochast (2) gradient (2) generat (2) neural (2) model (2) deep (2) uncertainti (1) determinist (1) backpropag (1)
Person: Daan Wierstra
DBLP: Wierstra:Daan
Contributed to:
20152014201420092004Wrote 7 papers:
- ICML-2015-BlundellCKW #network #nondeterminism
- Weight Uncertainty in Neural Network (CB, JC, KK, DW), pp. 1613–1622.
- ICML-2015-GregorDGRW #generative #image #named #network
- DRAW: A Recurrent Neural Network For Image Generation (KG, ID, AG, DJR, DW), pp. 1462–1471.
- ICML-c1-2014-SilverLHDWR #algorithm #policy
- Deterministic Policy Gradient Algorithms (DS, GL, NH, TD, DW, MAR), pp. 387–395.
- ICML-c2-2014-GregorDMBW #network
- Deep AutoRegressive Networks (KG, ID, AM, CB, DW), pp. 1242–1250.
- ICML-c2-2014-RezendeMW #approximate #generative #modelling #probability
- Stochastic Backpropagation and Approximate Inference in Deep Generative Models (DJR, SM, DW), pp. 1278–1286.
- ICML-2009-YiWSS #probability #using
- Stochastic search using the natural gradient (YS, DW, TS, JS), pp. 1161–1168.
- ICML-2004-WierstraW #markov #modelling
- Utile distinction hidden Markov models (DW, MW).