Recurrent Convolutional Neural Networks for Discourse Compositionality. - Nal Kalchbrenner; Phil Blunsom (CVSM@ACL, 2013)

Recurrent Continuous Translation Models. - Nal Kalchbrenner; Phil Blunsom (EMNLP, 2013)

A Convolutional Neural Network for Modelling Sentences. - Nal Kalchbrenner; Edward Grefenstette; Phil Blunsom (ACL (1), 2014)

Resolving Lexical Ambiguity in Tensor Regression Models of Meaning. - Dimitri Kartsaklis; Nal Kalchbrenner; Mehrnoosh Sadrzadeh (ACL (2), 2014)

Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. - Misha Denil; Alban Demiraj; Nal Kalchbrenner; Phil Blunsom; Nando de Freitas (CoRR, 2014)

Associative Long Short-Term Memory. - Ivo Danihelka; Greg Wayne; Benigno Uria; Nal Kalchbrenner; Alex Graves (ICML, 2016)

Pixel Recurrent Neural Networks. - Aäron van den Oord; Nal Kalchbrenner; Koray Kavukcuoglu (ICML, 2016)

Conditional Image Generation with PixelCNN Decoders. - Aäron van den Oord; Nal Kalchbrenner; Lasse Espeholt; Koray Kavukcuoglu; Oriol Vinyals; Alex Graves (NIPS, 2016)

WaveNet: A Generative Model for Raw Audio. - Aäron van den Oord; Sander Dieleman; Heiga Zen; Karen Simonyan; Oriol Vinyals; Alex Graves; Nal Kalchbrenner; Andrew W. Senior; Koray Kavukcuoglu (SSW, 2016)

Grid Long Short-Term Memory. - Nal Kalchbrenner; Ivo Danihelka; Alex Graves (ICLR (Poster), 2016)

Neural Machine Translation in Linear Time. - Nal Kalchbrenner; Lasse Espeholt; Karen Simonyan; Aäron van den Oord; Alex Graves; Koray Kavukcuoglu (CoRR, 2016)

Mastering the game of Go with deep neural networks and tree search. - David Silver; Aja Huang; Chris J. Maddison; Arthur Guez; Laurent Sifre; George van den Driessche 002; Julian Schrittwieser; Ioannis Antonoglou; Vedavyas Panneershelvam; Marc Lanctot; Sander Dieleman; Dominik Grewe; et al. (Nat., 2016)

Video Pixel Networks. - Nal Kalchbrenner; Aäron van den Oord; Karen Simonyan; Ivo Danihelka; Oriol Vinyals; Alex Graves; Koray Kavukcuoglu (ICML, 2017)

Parallel Multiscale Autoregressive Density Estimation. - Scott E. Reed; Aäron van den Oord; Nal Kalchbrenner; Sergio Gomez Colmenarejo; Ziyu Wang 001; Yutian Chen 001; Dan Belov; Nando de Freitas (ICML, 2017)

Parallel Multiscale Autoregressive Density Estimation. - Scott E. Reed; Aäron van den Oord; Nal Kalchbrenner; Sergio Gomez Colmenarejo; Ziyu Wang 001; Dan Belov; Nando de Freitas (CoRR, 2017)

Encoder-decoder neural networks. - Nal Kalchbrenner (2017)

Tensor2Tensor for Neural Machine Translation. - Ashish Vaswani; Samy Bengio; Eugene Brevdo; François Chollet; Aidan N. Gomez; Stephan Gouws; Llion Jones; Lukasz Kaiser; Nal Kalchbrenner; Niki Parmar; Ryan Sepassi; Noam Shazeer; et al. (AMTA (1), 2018)

Efficient Neural Audio Synthesis. - Nal Kalchbrenner; Erich Elsen; Karen Simonyan; Seb Noury; Norman Casagrande; Edward Lockhart; Florian Stimberg; Aäron van den Oord; Sander Dieleman; Koray Kavukcuoglu (ICML, 2018)

Parallel WaveNet: Fast High-Fidelity Speech Synthesis. - Aäron van den Oord; Yazhe Li; Igor Babuschkin; Karen Simonyan; Oriol Vinyals; Koray Kavukcuoglu; George van den Driessche 002; Edward Lockhart; Luis C. Cobo; Florian Stimberg; Norman Casagrande; Dominik Grewe; et al. (ICML, 2018)

Generating High fidelity Images with subscale pixel Networks and Multidimensional Upscaling. - Jacob Menick; Nal Kalchbrenner (ICLR, 2019)

Bayesian Inference for Large Scale Image Classification. - Jonathan Heek; Nal Kalchbrenner (CoRR, 2019)

Axial Attention in Multidimensional Transformers. - Jonathan Ho; Nal Kalchbrenner; Dirk Weissenborn; Tim Salimans (CoRR, 2019)

A Spectral Energy Distance for Parallel Speech Synthesis. - Alexey A. Gritsenko; Tim Salimans; Rianne van den Berg; Jasper Snoek; Nal Kalchbrenner (NeurIPS, 2020)

MetNet: A Neural Weather Model for Precipitation Forecasting. - Casper Kaae Sønderby; Lasse Espeholt; Jonathan Heek; Mostafa Dehghani 001; Avital Oliver; Tim Salimans; Shreya Agrawal; Jason Hickey; Nal Kalchbrenner (CoRR, 2020)

Colorization Transformer. - Manoj Kumar; Dirk Weissenborn; Nal Kalchbrenner (ICLR, 2021)

Towards Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (CoRR, 2021)

Gradual Domain Adaptation in the Wild: When Intermediate Distributions are Absent. - Samira Abnar; Rianne van den Berg; Golnaz Ghiasi; Mostafa Dehghani 001; Nal Kalchbrenner; Hanie Sedghi (CoRR, 2021)

Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks. - Lasse Espeholt; Shreya Agrawal; Casper Kaae Sønderby; Manoj Kumar; Jonathan Heek; Carla Bromberg; Cenk Gazen; Jason Hickey; Aaron Bell; Nal Kalchbrenner (CoRR, 2021)

Toward Causal Representation Learning. - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (Proc. IEEE, 2021)

On the surprising tradeoff between ImageNet accuracy and perceptual similarity. - Manoj Kumar; Neil Houlsby; Nal Kalchbrenner; Ekin D. Cubuk (CoRR, 2022)

Deep Learning-based Text Classification: A Comprehensive Review. - Shervin Minaee; Nal Kalchbrenner; Erik Cambria; Narjes Nikzad; Meysam Chenaghlu; Jianfeng Gao 001 (ACM Comput. Surv., 2022)

Do better ImageNet classifiers assess perceptual similarity better? - Manoj Kumar; Neil Houlsby; Nal Kalchbrenner; Ekin Dogus Cubuk (Trans. Mach. Learn. Res., 2022)

Deep Learning for Day Forecasts from Sparse Observations. - Marcin Andrychowicz; Lasse Espeholt; Di Li; Samier Merchant; Alex Merose; Fred Zyda; Shreya Agrawal; Nal Kalchbrenner (CoRR, 2023)

Stacking Diverse Architectures to Improve Machine Translation. - Andrea Schioppa; Nal Kalchbrenner (Trans. Mach. Learn. Res., 2023)