Taming unbalanced training workloads in deep learning with partial collective operations
S. Li, T.B.-N. Tal Ben-Nun, S.D. Girolamo, D.-A. Alistarh, T. Hoefler, in:, Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 45–61.

Non-blocking interpolation search trees with doubly-logarithmic running time
T.A. Brown, A. Prokopec, D.-A. Alistarh, in:, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 276–291.

Adaptive gradient quantization for data-parallel SGD
F. Faghri, I. Tabrizian, I. Markov, D.-A. Alistarh, D. Roy, A. Ramezani-Kebrya, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2020.

Stochastic games with lexicographic reachability-safety objectives
K. Chatterjee, J.P. Katoen, M. Weininger, T. Winkler, in:, International Conference on Computer Aided Verification, Springer Nature, 2020, pp. 398–420.

A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits
R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 4082–4093.

Learning representations for binary-classification without backpropagation
M. Lechner, in:, 8th International Conference on Learning Representations, ICLR, 2020.

Monitorability under assumptions
T.A. Henzinger, N.E. Sarac, in:, Runtime Verification, Springer Nature, 2020, pp. 3–18.

Lagrangian reachtubes: The next generation
S. Gruenbacher, J. Cyranka, M. Lechner, M.A. Islam, S.A. Smolka, R. Grosu, in:, Proceedings of the 59th IEEE Conference on Decision and Control, IEEE, 2020, pp. 1556–1563.

Hybridization for stability verification of nonlinear switched systems
M. Garcia Soto, P. Prabhakar, in:, 2020 IEEE Real-Time Systems Symposium, IEEE, 2020, pp. 244–256.

Neural circuit policies enabling auditable autonomy
M. Lechner, R. Hasani, A. Amini, T.A. Henzinger, D. Rus, R. Grosu, Nature Machine Intelligence 2 (2020) 642–652.

Inductive sequentialization of asynchronous programs
B. Kragl, C. Enea, T.A. Henzinger, S.O. Mutluergil, S. Qadeer, in:, Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2020, pp. 227–242.

Refinement for structured concurrent programs
B. Kragl, S. Qadeer, T.A. Henzinger, in:, Computer Aided Verification, Springer Nature, 2020, pp. 275–298.

An SMT theory of fixed-point arithmetic
M. Baranowski, S. He, M. Lechner, T.S. Nguyen, Z. Rakamari, in:, Automated Reasoning, Springer Nature, 2020, pp. 13–31.

Reinforcement learning of risk-constrained policies in Markov decision processes
T. Brázdil, K. Chatterjee, P. Novotný, J. Vahala, Proceedings of the 34th AAAI Conference on Artificial Intelligence 34 (2020) 9794–9801.

Proving expected sensitivity of probabilistic programs with randomized variable-dependent termination time
P. Wang, H. Fu, K. Chatterjee, Y. Deng, M. Xu, in:, Proceedings of the ACM on Programming Languages, ACM, 2020.

Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens
W. Jahr, P. Velicky, J.G. Danzl, Methods 174 (2020) 27–41.

Wave curves: Simulating Lagrangian water waves on dynamically deforming surfaces
T. Skrivan, A. Soderstrom, J. Johansson, C. Sprenger, K. Museth, C. Wojtan, ACM Transactions on Graphics 39 (2020).

The local structure of the energy landscape in multiphase mean curvature flow: weak-strong uniqueness and stability of evolutions
J.L. Fischer, S. Hensel, T. Laux, T. Simon, ArXiv (n.d.).

Replay of behavioral sequences in the medial prefrontal cortex during rule switching
K. Käfer, M. Nardin, K. Blahna, J.L. Csicsvari, Neuron 106 (2020) 4–165.e6.

The coupling mechanism of mammalian respiratory complex I
D. Kampjut, L.A. Sazanov, Science 370 (2020).