EBT has pretty much nothing to do with HNets, but it's also a recent (July) paper which struck a chord with me. Idea is to reconcile autoregressive crossentropy trained transformers (aka all LLMs these days) with scoring models (aka diffusion)
July 13, 2025 at 6:36 AM
EBT has pretty much nothing to do with HNets, but it's also a recent (July) paper which struck a chord with me. Idea is to reconcile autoregressive crossentropy trained transformers (aka all LLMs these days) with scoring models (aka diffusion)
Marina Meil\u{a}
The Entropy and Crossentropy of Generalized Mallows Models
https://arxiv.org/abs/2503.17521
The Entropy and Crossentropy of Generalized Mallows Models
https://arxiv.org/abs/2503.17521
March 25, 2025 at 6:24 AM
Marina Meil\u{a}
The Entropy and Crossentropy of Generalized Mallows Models
https://arxiv.org/abs/2503.17521
The Entropy and Crossentropy of Generalized Mallows Models
https://arxiv.org/abs/2503.17521
(Btw, I was saying it because of the below and how I observe people use the term. We can say it’s too general, I can agree with that. At least one should be aware that div. minimization problems have been ofc addressed outside and/or before the VI lit. (eg crossentropy)
bsky.app/profile/nico...
bsky.app/profile/nico...
November 21, 2024 at 7:52 AM
(Btw, I was saying it because of the below and how I observe people use the term. We can say it’s too general, I can agree with that. At least one should be aware that div. minimization problems have been ofc addressed outside and/or before the VI lit. (eg crossentropy)
bsky.app/profile/nico...
bsky.app/profile/nico...
"모델 성능이 안 나올 때 첫 번째로 의심해야 할 것!" MSE vs MAE vs Huber Loss, Binary vs Categorical Cross-Entropy, Focal Loss, Dice Loss까지. 회귀/분류 문제별 최적 손실함수 선택법, PyTorch/TensorFlow 구현 코드, 실전 문제 해결 전략까지 완벽 가이드.
#CrossEntropy #FocalLoss #LossFunction #MSE #PyTorch #TensorFlow #딥러닝러닝 #머신러닝러닝
doyouknow.kr/761/loss-fun...
December 7, 2025 at 3:13 PM
"모델 성능이 안 나올 때 첫 번째로 의심해야 할 것!" MSE vs MAE vs Huber Loss, Binary vs Categorical Cross-Entropy, Focal Loss, Dice Loss까지. 회귀/분류 문제별 최적 손실함수 선택법, PyTorch/TensorFlow 구현 코드, 실전 문제 해결 전략까지 완벽 가이드.
#CrossEntropy #FocalLoss #LossFunction #MSE #PyTorch #TensorFlow #딥러닝러닝 #머신러닝러닝
doyouknow.kr/761/loss-fun...
📖 Deep Learning with Python
by François Chollet
Confused by crossentropy? This quote clarifies how deep learning measures prediction error. Join the discussion on ML fundamentals.
by François Chollet
Confused by crossentropy? This quote clarifies how deep learning measures prediction error. Join the discussion on ML fundamentals.
Deep Learning with Python
by François Chollet · Amazon
amzn.to
August 4, 2026 at 12:07 PM
📖 Deep Learning with Python
by François Chollet
Confused by crossentropy? This quote clarifies how deep learning measures prediction error. Join the discussion on ML fundamentals.
by François Chollet
Confused by crossentropy? This quote clarifies how deep learning measures prediction error. Join the discussion on ML fundamentals.
Conditions Challenge. Our proposed architecture leverages cross-modality, utilizing cross-modal attention to fuse representations from different modalities. To address class imbalance, we employed two training designs: (i) weighted crossentropy loss [3/5 of https://arxiv.org/abs/2505.20007v1]
May 27, 2025 at 6:06 AM
Conditions Challenge. Our proposed architecture leverages cross-modality, utilizing cross-modal attention to fuse representations from different modalities. To address class imbalance, we employed two training designs: (i) weighted crossentropy loss [3/5 of https://arxiv.org/abs/2505.20007v1]
2️⃣ New Reranker Losses
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
🧵
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
🧵
March 26, 2025 at 3:02 PM
2️⃣ New Reranker Losses
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
🧵
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
🧵
