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Leo Feng
Observed names:
Feng, Leo,
Leo (Tsung-Cheng) Feng
Institutions:
Max Planck Institute for Intelligent Systems,
Tübingen AI Center,
ELLIS Institute Tübingen
Observed institutions:
University of Oxford,
Firmenich (United States),
Max Planck Institute for Intelligent Systems,
Mila - Quebec Artificial Intelligence Institute,
Tübingen AI Center,
ELLIS Institute Tübingen,
Université de Montréal
show all 7
OpenAlex ID:
A5006427579
Were RNNs All We Needed?
2024
·
Feng, Leo
, Tung, Frederick
, et al.
·
arXiv (Cornell University)
·
93
PDF
Attention as an RNN
2024
·
Feng, Leo
, Tung, Frederick
, et al.
·
arXiv (Cornell University)
·
27
PDF
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning
2021
·
Luisa Zintgraf
, Sebastian Schulze
, et al.
·
Journal of Machine Learning Research
·
20
Generative Active Learning for the Search of Small-molecule Protein Binders
2024
·
Korablyov, Maksym
, Liu, Cheng-Hao
, et al.
·
arXiv (Cornell University)
·
18
PDF
Towards Better Selective Classification
2022
·
Feng, Leo
, Ahmed, Mohamed Osama
, et al.
·
arXiv (Cornell University)
·
18
PDF
Latent Bottlenecked Attentive Neural Processes
2022
·
Feng, Leo
, Hajimirsadeghi, Hossein
, et al.
·
arXiv (Cornell University)
·
15
PDF
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
2020
·
Zintgraf, Luisa
, Feng, Leo
, et al.
·
arXiv (Cornell University)
·
13
PDF
Continuous-Time Meta-Learning with Forward Mode Differentiation
2022
·
Deleu, Tristan
, Kanaa, David
, et al.
·
arXiv (Cornell University)
·
12
PDF
Efficient DEM modeling of solid flavor particle mixing in a rotary drum
2024
·
Rutger van Sleeuwen
, Stefan Pantaleev
, et al.
·
Powder Technology
·
11
Memory Efficient Neural Processes via Constant Memory Attention Block
2023
·
Feng, Leo
, Tung, Frederick
, et al.
·
arXiv (Cornell University)
·
7
PDF
Adaptive teachers for amortized samplers
2024
·
Kim, Minsu
, Choi, Sanghyeok
, et al.
·
arXiv (Cornell University)
·
6
PDF
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization
2022
·
Feng, Leo
, Nouri, Padideh
, et al.
·
arXiv (Cornell University)
·
6
PDF
VIABLE: Fast Adaptation via Backpropagating Learned Loss
2019
·
Feng, Leo
, Zintgraf, Luisa
, et al.
·
arXiv (Cornell University)
·
3
PDF
Do LLMs Benefit from User and Item Embeddings in Recommendation Tasks?
2026
·
Hossain, Mir Rayat Imtiaz
, Feng, Leo
, et al.
·
arXiv (Cornell University)
·
2
PDF
Tree Cross Attention
2023
·
Feng, Leo
, Tung, Frederick
, et al.
·
arXiv (Cornell University)
·
2
PDF
Constant Memory Attention Block
2023
·
Feng, Leo
, Tung, Frederick
, et al.
·
arXiv (Cornell University)
·
1
PDF
From AutoResearch to Continual AutoResearch: Do Agents Learn Across Tasks?
2026
·
Qin, Jeremy
, Deng, Ruizhi
, et al.
·
arXiv (Cornell University)
PDF
Amortized Off-Policy Evaluation for LLMs
2026
·
Choi, Younwoo
, Feng, Leo
, et al.
·
arXiv (Cornell University)
PDF
SENTRY: Deterministic, Intelligent Risk Assessment for IT Change Management
2026
·
Arulpragasam, Daniel
, Henrysson, Christer
, et al.
·
arXiv (Cornell University)
PDF
Can LLMs Take Retrieved Information with a Grain of Salt?
2026
·
Shayegh, Behzad
, Ahmed, Mohamed Osama
, et al.
·
arXiv (Cornell University)
PDF
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Works count:
21
Citation count:
254
H-index:
9
I10-index:
9
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